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As an optimization that starts from a randomly selected structure generally does not guarantee reasonable optimality, the use of a systemic approach, named the ground structure, is widely accepted in steel-made truss and frame structural design. However, in the case of reinforced concrete (RC) structural optimization, because of the orthogonal orientation of structural members, randomly chosen or architect-sketched framing is used. Such a one-time fixed layout trend, in addition to its lack of a systemic approach, does not necessarily guarantee optimality. In this study, an approach for generating a candidate ground structure to be used for cost or weight minimization of 3D RC building structures with included slabs is developed. A multiobjective function at the floor optimization stage and a single objective function at the frame optimization stage are considered. A particle swarm optimization (PSO) method is employed for selecting the optimal ground structure. This method enables generating a simple, yet potential, real-world representation of topologically preoptimized ground structure while both structural and main architectural requirements are considered. This is supported by a case study for different floor domain sizes.
Tensile strain and compress strain can greatly affect the thermal conductivity of graphene nanoribbons (GNRs). However, the effect of GNRs under shear strain, which is also one of the main strain effect, has not been studied systematically yet. In this work, we employ reverse nonequilibrium molecular dynamics (RNEMD) to the systematical study of the thermal conductivity of GNRs (with model size of 4 nm × 15 nm) under the shear strain. Our studies show that the thermal conductivity of GNRs is not sensitive to the shear strain, and the thermal conductivity decreases only 12–16% before the pristine structure is broken. Furthermore, the phonon frequency and the change of the micro-structure of GNRs, such as band angel and bond length, are analyzed to explore the tendency of thermal conductivity. The results show that the main influence of shear strain is on the in-plane phonon density of states (PDOS), whose G band (higher frequency peaks) moved to the low frequency, thus the thermal conductivity is decreased. The unique thermal properties of GNRs under shear strains suggest their great potentials for graphene nanodevices and great potentials in the thermal managements and thermoelectric applications.
The Marmara Region (NW Turkey) has experienced significant earthquakes (M > 7.0) to date. A destructive earthquake is also expected in the region. To determine the effect of the specific design spectrum, eleven provinces located in the region were chosen according to the Turkey Earthquake Building Code updated in 2019. Additionally, the differences between the previous and updated regulations of the country were investigated. Peak Ground Acceleration (PGA) and Peak Ground Velocity (PGV) were obtained for each province by using earthquake ground motion levels with 2%, 10%, 50%, and 68% probability of exceedance in 50-year periods. The PGA values in the region range from 0.16 to 0.7 g for earthquakes with a return period of 475 years. For each province, a sample of a reinforced-concrete building having two different numbers of stories with the same ground and structural characteristics was chosen. Static adaptive pushover analyses were performed for the sample reinforced-concrete building using each province’s design spectrum. The variations in the earthquake and structural parameters were investigated according to different geographical locations. It was determined that the site-specific design spectrum significantly influences target displacements for performance-based assessments of buildings due to seismicity characteristics of the studied geographic location.
The upper limit of the thermal conductivity and the mechanical strength are predicted for the polyethylene chain, by performing the ab initio calculation and applying the quantum mechanical non-equilibrium Green’s function approach. Specially, there are two main findings from our calculation: (1) the thermal conductivity can reach a high value of 310 Wm−1 K−1 in a 100 nm polyethylene chain at room temperature and the thermal conductivity increases with the length of the chain; (2) the Young’s modulus in the polyethylene chain is as high as 374.5 GPa, and the polyethylene chain can sustain 32.85%±0.05% (ultimate) strain before undergoing structural phase transition into gaseous ethylene.
In this study, the behavior of a widely graded soil prone to suffusion and necessity of homogeneity quantifi cation for such a soil in internal stability considerations are discussed. With the help of suffusion tests, the dependency of the particle washout to homogeneity of sample is shown. The validity of the great infl uence of homogeneity on suffusion processes by the presentation of arguments and evidences are established. It is emphasized that the internal stability of a widely graded soil cannot be directly correlated to the common geotechnical parameters such as dry density or permeability. The initiation and propagation of the suffusion processes are clearly a particle scale phenomenon, so the homogeneity of particle assemblies (micro-scale) has a decisive effect on particle rearrangement and washout processes. It is addressed that the guidelines for assessing internal stability lack a fundamental, scientifi c basis for quantifi cation of homogeneity. The observation of the segregation processes within the sample in an ascending layered order (for downwards fl ow) inspired the author to propose a new packing model for granular materials which are prone to internally instability.
It is shown that the particle arrangement, especially the arrangement of soil skeleton particles or the so-called primary fabric has the main role in suffusiv processes. Therefore, an experimental approach for identifi cation of the skeleton in the soil matrix is proposed. 3D models of Sequential Fill Tests using Discrete Element Method (DEM) and 3D models of granular packings for relative, stochastically and ideal homogeneous particle assemblies were generated, and simulations have been carried out.
Based on the numerical investigations and in dependency on the soil skeleton behavior, an approach for measurement of relevant scale, the so-called Representative Elementary Volume (REV) for homogeneity investigation is proposed. The development of a new testing method for quantifi cation of homogeneity is introduced (in-situ). An approach for quantifi cation of homogeneity in numerically or experimentally generated packings (samples) based on image processing method of MATLAB has been introduced. A generalized experimental method for assessment of internal stability for widely graded soils with dominant coarse matrix is developed, and a new suffusion criterion based on ideal homogeneous internally stable granular packing is designed.
My research emphasizes that in a widely graded soils with dominant coarse matrix, the soil fractions with diameters bigger than D60 build essentially the soil skeleton. The mass and spatial distribution of these fractions governs the internal stability, and the mass and distribution of the fi ll fractions are a secondary matter. For such a soil, the homogeneity of the skeleton must be cautiously measured and verified.
Nanostructured materials are extensively applied in many fields of material science for new industrial applications, particularly in the automotive, aerospace industry due to their exceptional physical and mechanical properties. Experimental testing of nanomaterials is expensive, timeconsuming,challenging and sometimes unfeasible. Therefore,computational simulations have been employed as alternative method to predict macroscopic material properties. The behavior of polymeric nanocomposites (PNCs) are highly complex.
The origins of macroscopic material properties reside in the properties and interactions taking place on finer scales. It is therefore essential to use multiscale modeling strategy to properly account for all large length and time scales associated with these material systems, which across many orders of magnitude. Numerous multiscale models of PNCs have been established, however, most of them connect only two scales. There are a few multiscale models for PNCs bridging four length scales (nano-, micro-, meso- and macro-scales). In addition, nanomaterials are stochastic in nature and the prediction of macroscopic mechanical properties are influenced by many factors such as fine-scale features. The predicted mechanical properties obtained by traditional approaches significantly deviate from the measured values in experiments due to neglecting uncertainty of material features. This discrepancy is indicated that the effective macroscopic properties of materials are highly sensitive to various sources of uncertainty, such as loading and boundary conditions and material characteristics, etc., while very few stochastic multiscale models for PNCs have been developed. Therefore, it is essential to construct PNC models within the framework of stochastic modeling and quantify the stochastic effect of the input parameters on the macroscopic mechanical properties of those materials.
This study aims to develop computational models at four length scales (nano-, micro-, meso- and macro-scales) and hierarchical upscaling approaches bridging length scales from nano- to macro-scales. A framework for uncertainty quantification (UQ) applied to predict the mechanical properties
of the PNCs in dependence of material features at different scales is studied. Sensitivity and uncertainty analysis are of great helps in quantifying the effect of input parameters, considering both main and interaction effects, on the mechanical properties of the PNCs. To achieve this major
goal, the following tasks are carried out:
At nano-scale, molecular dynamics (MD) were used to investigate deformation mechanism of glassy amorphous polyethylene (PE) in dependence of temperature and strain rate. Steered molecular dynamics (SMD)were also employed to investigate interfacial characteristic of the PNCs.
At mico-scale, we developed an atomistic-based continuum model represented by a representative volume element (RVE) in which the SWNT’s properties and the SWNT/polymer interphase are modeled at nano-scale, the surrounding polymer matrix is modeled by solid elements. Then, a two-parameter model was employed at meso-scale. A hierarchical multiscale approach has been developed to obtain the structure-property relations at one length scale and transfer the effect to the higher length
scales. In particular, we homogenized the RVE into an equivalent fiber.
The equivalent fiber was then employed in a micromechanical analysis (i.e. Mori-Tanaka model) to predict the effective macroscopic properties of the PNC. Furthermore, an averaging homogenization process was also used to obtain the effective stiffness of the PCN at meso-scale.
Stochastic modeling and uncertainty quantification consist of the following ingredients:
- Simple random sampling, Latin hypercube sampling, Sobol’ quasirandom sequences, Iman and Conover’s method (inducing correlation in Latin hypercube sampling) are employed to generate independent and dependent sample data, respectively.
- Surrogate models, such as polynomial regression, moving least squares (MLS), hybrid method combining polynomial regression and MLS, Kriging regression, and penalized spline regression, are employed as an approximation of a mechanical model. The advantage of the surrogate models is the high computational efficiency and robust as they can be constructed from a limited amount of available data.
- Global sensitivity analysis (SA) methods, such as variance-based methods for models with independent and dependent input parameters, Fourier-based techniques for performing variance-based methods and partial derivatives, elementary effects in the context of local SA, are used to quantify the effects of input parameters and their interactions on the mechanical properties of the PNCs. A bootstrap technique is used to assess the robustness of the global SA methods with respect to their performance.
In addition, the probability distribution of mechanical properties are determined by using the probability plot method. The upper and lower bounds of the predicted Young’s modulus according to 95 % prediction intervals were provided.
The above-mentioned methods study on the behaviour of intact materials. Novel numerical methods such as a node-based smoothed extended finite element method (NS-XFEM) and an edge-based smoothed phantom node method (ES-Phantom node) were developed for fracture problems. These methods can be used to account for crack at macro-scale for future works. The predicted mechanical properties were validated and verified. They show good agreement with previous experimental and simulations results.
The polymeric clay nanocomposites are a new class of materials of which recently have become the centre of attention due to their superior mechanical and physical properties. Several studies have been performed on the mechanical characterisation of these nanocomposites; however most of those studies have neglected the effect of the interfacial region between the clays and the matrix despite of its significant influence on the mechanical performance of the nanocomposites.
There are different analytical methods to calculate the overall elastic material properties of the composites. In this study we use the Mori-Tanaka method to determine the overall stiffness of the composites for simple inclusion geometries of cylinder and sphere. Furthermore, the effect of interphase layer on the overall properties of composites is calculated. Here, we intend to get ounds for the effective mechanical properties to compare with the analytical results. Hence, we use linear displacement boundary conditions (LD) and uniform traction boundary conditions (UT) accordingly. Finally, the analytical results are compared with numerical results and they are in a good agreement.
The next focus of this dissertation is a computational approach with a hierarchical multiscale method on the mesoscopic level. In other words, in this study we use the stochastic analysis and computational homogenization method to analyse the effect of thickness and stiffness of the interfacial region on the overall elastic properties of the clay/epoxy nanocomposites. The results show that the increase in interphase thickness, reduces the stiffness of the clay/epoxy naocomposites and this decrease becomes significant in higher clay contents. The results of the sensitivity analysis prove that the stiffness of the interphase layer has more significant effect on the final stiffness of nanocomposites. We also validate the results with the available experimental results from the literature which show good agreement.
This paper presents a novel numerical procedure based on the framework of isogeometric analysis for static, free vibration, and buckling analysis of laminated composite plates using the first-order shear deformation theory. The isogeometric approach utilizes non-uniform rational B-splines to implement for the quadratic, cubic, and quartic elements. Shear locking problem still exists in the stiffness formulation, and hence, it can be significantly alleviated by a stabilization technique. Several numerical examples are presented to show the performance of the method, and the results obtained are compared with other available ones.
Spatial time domain reflectometry (spatial TDR) is a new measurement method for determining water content profiles along elongated probes (transmission lines). The method is based on the inverse modeling of TDR reflectograms using an optimization algorithm. By means of using flat ribbon cables it is possible to take two independent TDRmeasurements from both ends of the probe, which are used to improve the spatial information content of the optimization results and to consider effects caused by electrical conductivity. The method has been used for monitoring water content distributions on a full-scale levee model made of well-graded clean sand. Flood simulation tests, irrigation tests, and long-term observations were carried out on the model. The results show that spatial TDR is able to determine water content distributions with an accuracy of the spatial resolution of about ±3 cm compared to pore pressure measurements and an average deviation of ±2 vol % compared to measurements made using another independent TDR measurement system.
The present article aims to provide an overview of the consequences of dynamic soil-structure interaction (SSI) on building structures and the available modelling techniques to resolve SSI problems. The role of SSI has been traditionally considered beneficial to the response of structures. However, contemporary studies and evidence from past earthquakes showed detrimental effects of SSI in certain conditions. An overview of the related investigations and findings is presented and discussed in this article. Additionally, the main approaches to evaluate seismic soil-structure interaction problems with the commonly used modelling techniques and computational methods are highlighted. The strength, limitations, and application cases of each model are also discussed and compared. Moreover, the role of SSI in various design codes and global guidelines is summarized. Finally, the advancements and recent findings on the SSI effects on the seismic response of buildings with different structural systems and foundation types are presented. In addition, with the aim of helping new researchers to improve previous findings, the research gaps and future research tendencies in the SSI field are pointed out.
We perform both classical molecular dynamics simulations and beam model calculations to investigate the Young's modulus of kinked silicon nanowires (KSiNWs). The Young's modulus is found to be highly sensitive to the arm length of the kink and is essentially inversely proportional to the arm length. The mechanism underlying the size dependence is found to be the interplay between the kink angle potential and the arm length potential, where we obtain an analytic relationship between the Young's modulus and the arm length of the KSiNW. Our results provide insight into the application of this novel building block in nanomechanical devices.
Der vorliegende Beitrag beschreibt die Problematik bei der Prognose verkehrsbedingter Schadstoff-Immissionen. Im Mittelpunkt steht die Entwicklung und der Aufbau einer Simulationsumgebung zur Evaluation von umweltorientierten Verkehrsmanagement-Strategien. Die Simulationsumgebung wird über die drei Felder Verkehr, Emission, Immission entwickelt und findet zunächst Anwendung in der Evaluation verkehrlicher Maßnahmen für die Friedberger Landstraße in Frankfurt am Main.
Scaling of concrete due to salt frost attack is an important durability issue in moderate and cold climates. The actual damage mechanism is still not completely understood. Two recent damage theories—the glue spall theory and the cryogenic suction theory—offer plausible, but conflicting explanations for the salt frost scaling mechanism. The present study deals with the cryogenic suction theory, which assumes that freezing concrete can take up unfrozen brine from a partly frozen deicing solution during salt frost attack. According to the model hypothesis, the resulting saturation of the concrete surface layer intensifies the ice formation in this layer and causes salt frost scaling. In this study an experimental technique was developed that makes it possible to quantify to which extent brine uptake can increase ice formation in hardened cement paste (used as a model material for concrete). The experiments were carried out with low temperature differential scanning calorimetry, where specimens were subjected to freeze–thaw cycles while being in contact with NaCl brine. Results showed that the ice content in the specimens increased with subsequent freeze–thaw cycles due to the brine uptake at temperatures below 0 °C. The ability of the hardened cement paste to bind chlorides from the absorbed brine at the same time affected the freezing/melting behavior of the pore solution and the magnitude of the ice content.
To assess the safety impact of auxiliary lanes at downstream locations of U-turns, the Traffic Conflict Technique was used. On the basis of the installed components at those locations, four types of U-turns were identified: those without any auxiliary lane, those with an acceleration lane, those with outer widening, and those with both an acceleration lane and outer widening. The available crash data is unreliable, therefore to assess the level of road safety, Conflict Indexes were formulated to put more emphasis on severe crashes than on slight ones by using two types of weighting coefficients. The first coefficient was based on the subjective assessment of the seriousness of the conflict situation and the second was based on the relative speed and angle between conflicting streams. A comparatively higher Conflict Index value represents a lower level of road safety. According to the results, a lower level of road safety occurs if two components apply or if a location is without any auxiliary lane. The highest level of road safety occurs if the layout includes only a single component, either an acceleration lane or outer widening.
Reinforced concrete walls are commonly selected as the lateral resisting systems in seismic design of buildings. The design procedure requires reliable/robust models to predict the wall response. Many researchers, thus, have focused on using the available experimental data to be able to comment on the quality of models at hand. What is missing though is an uncertain attitude towards the experimental data since such data can be affected by different sources of uncertainty. In this paper, we introduce the database created for model quality evaluation purposes considering the uncertainties in the experimental data. This is the first step of a larger study on experience-based model quality evaluation of reinforced concrete walls. Here, we briefly present the database as well as six sample validations of the developed numerical model (the quality of which is to be assessed). The database contains the information on nearly 300 wall specimens from about 50 sources. Both the database and the numerical model, built for uncertainty/sensitivity analysis purposes, are mainly based on ten parameters. These include geometry, material, reinforcement layout and loading properties. The validation results prove that the model is able to predict the wall response satisfactorily. Consequently, the validated numerical model could be used in further quality evaluation studies.
Die Gase Sauerstoff und Stickstoff werden für eine Vielzahl an technischen, industriellen, biologischen und medizinischen Einsatzzwecken benötigt. So liegen Anwendungsgebiete dieser Gase neben der klassischen metallverarbeitenden und der chemischen Industrie bei Sauerstoff vor allem in der Medizin, Verbrennungs- und Kläranlagenoptimierung sowie der Fischzucht und bei Stickstoff als Schutz- beziehungsweise Inertgas in der Kunststoffindustrie, der Luft- und Raumfahrt sowie dem Brandschutz.
Die Bereitstellung der Gase Sauerstoff und Stickstoff wird nahezu ausschließlich durch die Abtrennung aus der Umgebungsluft realisiert, welche aus ca. 78 Vol.-% Stickstoff, 21 Vol.-% Sauerstoff und 1 Vol.-% Spurengasen (Ar, CO2, Ne, He, ...) besteht. Am Markt etablierte Verfahren der Luftzerlegung sind das Linde-, das PSA- (pressure swing adsorption/Druckwechseladsorption) oder verschiedene Membran-Verfahren. Hierdurch werden die benötigten Gase entweder direkt vor Ort beim Verbraucher erzeugt (PSA- und Polymer-Membranverfahren: geringe Reinheiten) oder zentral in großen Anlagen hergestellt (Linde-Verfahren: hohe Reinheiten) und anschließend zum Verbraucher in Form von Flaschen- oder Tankgasen geliefert (Tansportkosten).
Für kleinere Verbraucher mit hohen Ansprüchen an die Reinheit des benötigten Sauerstoffs beziehungsweise Stickstoffs ergibt sich nur die Möglichkeit, die Gase als kostenintensive Transportgase zentraler Gaseversorger zu beziehen und sich somit in eine Abhängigkeit (Lieferverträge, Flaschen-/Tankmieten, ...) zu diesen zu begeben sowie eine eigene Lagerhaltung für die benötigten Gase (Mehraufwand, Lagerkosten, Platzbedarf) zu betreiben.
Ziel dieser Arbeit ist es, keramische Material-Systeme auf Basis chemischer Hochtemperatur-Reaktionen als Reaktive Oxidkeramiken zu entwickeln und diese hinsichtlich eines möglichen Einsatzes für die Sauerstoffseparation in neuartigen Luftzerlegungsanlagen zu untersuchen.
Derartige Anlagen sollen in ihrem Prinzip an die regenerative Sauerstoffseparation angelehnt sein und in ihren Reaktoren die Reaktiven Oxidkeramiken als Festbett-Material abwechselnd mit Luft be- und Vakuum oder O2-armen Atmosphären entladen.
Die Verwendung Reaktiver Oxidkeramiken, welche im Vergleich zu den bisherigen Materialien höhere Sauerstoffaustauschmengen und -raten bei gleichzeitig hoher Lebensdauer und Korrosionsbeständigkeit sowie relativ einfacher Handhabe aufweisen würden, soll ein Schritt in Richtung einer effizienten alternativen Luftzerlegungstechnologie sein.
Mit den Reaktiven Oxidkeramiken in einer Luftzerlegungsanlage sollte es im besten Fall möglich sein, in kleinen Anlagen sehr reinen Sauerstoff und zugleich sauerstofffreies Inertgas zu erzeugen sowie eine Sauerstoffan- oder -abreicherung von Luft, Prozess- oder Abgasen zu generieren.
Somit besäße eine solche, auf Reaktiven Oxidkeramiken basierende Technologie sehr weit gefächerte Einsatzgebiete und demzufolge ein enormes wirtschaftliches Potential.
Das Bauwesen hat sich in den letzten Jahren durch die Globalisierung des Marktes verbunden mit einer verstärkten Nutzung moderner Technologien stark gewandelt. Die Planung und die Durchführung von Bauvorhaben werden zunehmend komplexer und sind mit erhöhten Risiken verbunden. Geld- und Zeitressourcen werden bei einem immer härter werdenden Konkurrenzkampf knapper.
Das Projektmanagement stellt Lösungsansätze bereit, um Bauvorhaben auch unter erschwerten Bedingungen und erhöhten Risiken erfolgreich zum Abschluss zu bringen. Dabei hat ein systematisches Risikomanagement beginnend bei der Projektentwicklung bis zum Projektabschluss eine für den Projekterfolg entscheidende Bedeutung.
Ziel der Arbeit ist es, eine quantitative Risikoerfassung für Projektmanager als professionelle Bauherrenvertretung und die Simulation der Risikoauswirkungen auf den Verlauf eines Projektes während der Planungs- und Bauphase zu ermöglichen. Mit Hilfe eines abstrakten Modells soll eine differenzierte, praxisnahe Simulation durchführbar sein, die die verschiedenen Arten der Leistungs- und Kostenentstehung widerspiegelt. Parallel dazu soll die Beschreibung von Risiken so abstrahiert werden, dass beliebige Risiken quantitativ erfassbar und anschließend ihre Auswirkungen inklusive mögliche Gegenmaßnahmen in das Modell integrierbar sind.
Anhand zweier Beispiele werden die unterschiedlichen Einsatzmöglichkeiten der quantitativen Erfassung von Projektrisiken und der anschließenden Simulation ihrer Auswirkungen aufgezeigt. Bei dem ersten Beispiel, einem realen, bereits abgeschlossenen Schieneninfrastrukturprojekt, wird die Wirksamkeit einer vorbeugenden Maßnahme gegen ein Projektrisiko untersucht. Im zweiten Beispiel wird ein Planspielansatz zur praxisnahen Aus- und Weiterbildung von Projektmanagern entwickelt. Inhalt des Planspiels ist die Planung und Errichtung eines privatfinanzierten, öffentlichen Repräsentationsbaus mit teilweiser Fremdnutzung.
"Qualitätsmanagement (QM) ist im Sinne reibungslos funktionierender Abläufe ein unverzichtbarer Bestandteil jedes Büros, unabhängig von der Größe und dem Kerngeschäft und unabhängig davon, ob ein Zertifizierungsverfahren durchlaufen
wird oder nicht. Im Laufe der Jahre werden in Ingenieur- und Architekturbüros meist zahlreiche organisatorische Einzelregelungen getroffen, die den Alltag erleichtern sollen. Eine systematische Zusammenstellung, Einführung und Kontrolle unterbleibt jedoch oft. Häufig schrecken die Verantwortlichen vor dem vermeintlichen Aufwand für die systematische Zusammenstellung in einem QM-Handbuch und dem vermeintlich noch viel größeren Aufwand für eine externe Überprüfung im Rahmen eines externen Audits mit anschließender Zertifizierung zurück. Der
Nutzen, der alleine schon durch ein passgenau aufgebautes und gelebtes QMHandbuch entsteht, wird nicht realisiert.
Der QM-Standard „Planer am Bau“ (PaB) ist ein branchenspezifischer Standard, der gezielt für Ingenieur- und Architekturbüros entwickelt worden ist und ausschließlich deren Belange berücksichtigt. Im Ergebnis entstehen nach klaren Vorgaben der Mindestanforderungen schlanke, auf die jeweiligen Bürobesonderheiten angepasste Handbücher, die durch den TÜV Rheinland auditiert und zertifiziert werden
können. Der Nachweis eines wirksamen QM-Systems ist mit diesem Zertifikat erbracht, was unter anderem in VgV-Ausschreibungen Vorteile bringen kann."
Marine macroalgae such as Ulva intestinalis have promising properties as feedstock for cosmetics and pharmaceuticals. However, since the quantity and quality of naturally grown algae vary widely, their exploitability is reduced – especially for producers in high-priced markets. Moreover, the expansion of marine or shore-based cultivation systems is unlikely in Europe, since promising sites either lie in fishing zones, recreational areas, or natural reserves. The aim was therefore to develop a closed photobioreactor system enabling full control of abiotic environmental parameters and an effective reconditioning of the cultivation medium in order to produce marine macroalgae at sites distant from the shore. To assess the feasibility and functionality of the chosen technological concept, a prototypal plant has been implemented in central Germany – a site distant from the sea. Using a newly developed, submersible LED light source, cultivation experiments with Ulva intestinalis led to growth rates of 7.72 ± 0.04 % day−1 in a cultivation cycle of 28 days. Based on the space demand of the production system, this results in fresh mass productivity of 3.0 kg m−2, respectively, of 1.1 kg m−2 per year. Also considering the ratio of biomass to energy input amounting to 2.76 g kWh−1, significant future improvements of the developed photobioreactor system should include the optimization of growth parameters, and the reduction of the system’s overall energy demand.
We present a physics-informed deep learning model for the transient heat transfer analysis of three-dimensional functionally graded materials (FGMs) employing a Runge–Kutta discrete time scheme. Firstly, the governing equation, associated boundary conditions and the initial condition for transient heat transfer analysis of FGMs with exponential material variations are presented. Then, the deep collocation method with the Runge–Kutta integration scheme for transient analysis is introduced. The prior physics that helps to generalize the physics-informed deep learning model is introduced by constraining the temperature variable with discrete time schemes and initial/boundary conditions. Further the fitted activation functions suitable for dynamic analysis are presented. Finally, we validate our approach through several numerical examples on FGMs with irregular shapes and a variety of boundary conditions. From numerical experiments, the predicted results with PIDL demonstrate well agreement with analytical solutions and other numerical methods in predicting of both temperature and flux distributions and can be adaptive to transient analysis of FGMs with different shapes, which can be the promising surrogate model in transient dynamic analysis.
A phantom-node method is developed for three-node shell elements to describe cracks. This method can treat arbitrary cracks independently of the mesh. The crack may cut elements completely or partially. Elements are overlapped on the position of the crack, and they are partially integrated to implement the discontinuous displacement across the crack. To consider the element containing a crack tip, a new kinematical relation between the overlapped elements is developed. There is no enrichment function for the discontinuous displacement field. Several numerical examples are presented to illustrate the proposed method.
A more careful consideration of food waste is needed for planning the urban environment. The research signals links between the organization of individuals, the built environment and food waste management through a study conducted in Mexico. It recognizes the different scales within which solid waste management operates, explores food waste production at household levels, and investigates the urban circumstances that influence its management. This is based on the idea that sustainable food waste management in cities requires a constellation of processes through which a ‘people centered’ approach offers added value to technical and biological facts. This distinction addresses how urban systems react to waste and what behavioral and structural factors affect current sanitary practices in Mexico. Food waste is a resource-demanding item, which makes for a considerable amount of refuse being disposed of in landfills in developing cities. The existing data shortage on waste generation at household levels debilitates implementation strategies and there is a need for more contextual knowledge associated with waste. The evidence-based study includes an explorative phase on the culture of waste management and a more in-depth examination of domestic waste composition. Mixed data collection tools including a household based survey, a food waste diary and weighing recording system were developed to enquire into the daily practices of waste disposal in households. The contrasting urban environment of Mexico City Metropolitan Area holds indistinctive boundaries between the core and the periphery, which hinder the implementation of integrated environmental plans. External determinants are different modes of urban transformation and internal determinants are building features and their consolidation processes. At the household level, less and more affluents groups responded differently to external environmental stressors. A targeted planning proposition is required for each group. Local alternative waste management is more likely to be implement in less affluent contexts. Further, more effective demand-driven service delivery implies better integration between the formal and informal sectors. The results show that efforts toward securing long-term changes in Mexico and other cities with similar circumstances require creating synergy between education, building consolidation, local infrastructure and social engagement.