Architectural Constraints Research Articles

MLGen: Generative Design Framework Based on Machine Learning and Topology Optimization

Design and manufacturing processes are entering into a new era as novel methods and techniques are constantly introduced. Currently, 3D printing is already established in the production processes of several industries while more are continuously being added. At the same time, topology optimization has become part of the design procedure of various industries, such as automotive and aeronautical. Parametric design has been gaining ground in the architectural design literature in the past years. Generative design is introduced as the contemporary design process that relies on the utilization of algorithms for creating several forms that respect structural and architectural constraints imposed, among others, by the design codes and/or as defined by the designer. In this study, a novel generative design framework labeled as MLGen is presented. MLGen integrates machine learning into the generative design practice. MLGen is able to generate multiple optimized solutions which vary in shape but are equivalent in terms of performance criteria. The output of the proposed framework is exported in a format that can be handled by 3D printers. The ability of MLGen to efficiently handle different problems is validated via testing on several benchmark topology optimization problems frequently employed in the literature.

Seed production of co-occurring species: Regenerative strategies, plant economic spectrum or architectural constraints?

Although plant clonality is an important reproductive strategy complementing seed reproduction, their interrelationship is seldom studied. We evaluated how plant clonality, together with plant economics spectrum and architectural constraints, affect the generative reproduction characteristics of co-existing grassland species. For this purpose, we collected data on seed number, seed mass and seed yield (seed mass x seed number) per shoot of 56 herbaceous species from temperate grasslands in the White Carpathian Mts. (SE Czech Republic).Clonality had a weaker effect on seed traits than leaf economics and plant architecture. Metamer size showed the strongest relationship to seed number per shoot, while leaf dry matter content and canopy height were the most important factors affecting average seed mass in the studied species. Seed yield was affected by both leaf nitrogen and metamer size but only for plants with long lived shoots (di- and polycyclic). The negative correlation between seed mass and seed number per shoot for our dataset was confirmed.Our study did not support the idea that clonality is the most important factor affecting seed production in grassland species and pointed out complex relationships of coordinated traits in coexisting species.

Sustainable layout design of steel buildings through embodied energy and costs optimization

Structural design process is a major phase in construction that has an impact not only on the cost of the project but on the environmental aspects as well. Although the majority of structural engineers aims to reduce the structural cost by reducing the weight of the elements, yet a handful of engineers has the information required to consider the environmental impact of their decisions. This paper presents an attempt to develop a multi-objective optimization model for steel floor structural system against cost and embodied energy using genetic algorithm. In addition, a novel study is conducted to address the embodied energy values for structural materials is Egypt. The presented model allows for determining the optimum layout of certain space taking into consideration the architectural constraints imposed on this space. In this optimization problem, the layout configuration of the steel beams, the steel beams profiles, the metal deck thickness, and the concrete slab thickness are determined. The developed model is elaborated along with the results of applying the model on two problems, which shows its ability to address several types of applications.

A practical shear wall layout optimization framework for the design of high-rise buildings

In the design of high-rise buildings, the lateral structural system that resists seismic and wind actions often dominates the overall design, and as a result, the optimum design of the lateral structural system is important for material efficiency. This paper aims to present a new design methodology that relies on an extended Evolutionary Structural Optimization (ESO) method to optimize the shear wall layout for the design of high-rise buildings. By discretizing all the shear walls of the ground structure into wall elements, different shear wall layouts were described by a binary matrix where ‘0′ and ‘1′ indicate the absence or presence of a wall element respectively. The proposed framework borrowed the intuitive concept of the ESO method, where the less stressed wall elements in the structure were gradually removed but the highly stressed wall elements were reserved. The conceptual design method was combined with the optimization algorithm to control the optimization process and to reduce structural eccentricity considering architecture, strength and serviceability constraints. Then, the structural weight could be automatically minimized under multiple loading cases and design constraints. By integrating the commercially available ETABS, a dedicated optimization software with an independent interface was developed and details were also presented in this paper for practical software development. The proposed framework was used to optimize the layouts of different shear wall structures, and case studies showed that the proposed framework could optimize shear wall structures with a material saving of up to 14% compared to the conventional design, which proved the feasibility and effectiveness of the framework. The paper can therefore be referenced by other researchers and software engineers to further explore the layout optimization of shear wall structures and to reduce material usage for a more sustainable design.

HUMAN ORIENTED ARCHITECTURAL LIGHTING DESIGN IN AMPHI-CLASSROOM LEARNING AREAS

By using artificial lighting in AMFI classrooms where there are architectural constraints and daylight cannot be adequately benefited from, it can contribute to the visual comfort and indirectly to the health of the students. In this study, point-based analysis of the Equivalent Melanopic Lux values of artificial lighting and learning environments in schools was made according to the criteria of WELL standards specified in the Human Centric Lighting concept. By using direct lighting, without changing the architectural design, optimum lighting suitable for human biology is provided with low-cost artificial lighting arrangements. According to the Human-Centered Lighting concept, an architectural lighting design was made in accordance with the WELL standards criteria. As a result of the improvement of visual comfort and optimum circadian effects in the learning environments of the students studying in AMFI classrooms, it is predicted that the success and participation of the students who use these learning areas will increase.

Beyond the beak: Brain size and allometry in avian craniofacial evolution.

Birds exhibit an enormous variety of beak shapes. Such remarkable variation, however, has distracted research from other important aspects of their skull evolution, the nature of which has been little explored. Key aspects of avian skull variation appear to be qualitatively similar to those of mammals, encompassing variation in the degree of cranial vaulting, cranial base flexure, and the proportions and orientations of the occipital and facial regions. The evolution of these traits has been studied intensively in mammals under the Spatial Packing Hypothesis (SPH), an architectural constraint so-called because the general anatomical organization and development of such skull parts makes them evolve predictably in response to changes in relative brain size. Such SPH predictions account for the different appearances of skull configurations across species, either in having longer or shorter faces, and caudally or ventrally oriented occiputs, respectively. This pattern has been morphometrically and experimentally proven in mammals but has not been examined in birds or other tetrapods, and so its generality remains unknown. We explored the SPH in an interspecific sample of birds using three-dimensional geometric morphometrics. Our results show that the dominant trend of evolutionary variation in the skull of crown-group birds can be predicted by the SPH, involving concomitant changes in the face, the cranial vault and the basicranium, and with striking similarities to craniofacial variation among mammals. Although craniofacial variation is significantly affected by allometry, these allometric effects are independent of the influence of the SPH on skull morphology, as are any effects of volumetric encephalization. Our results, therefore, validate the hypothesis that a general architectural constraint underlies skull homoplasy evolution of cranial morphology among avian clades, and possibly between birds and mammals, but they downplay encephalization and allometry as the only factors involved.

Adaptation of ED design layout during the COVID-19 pandemic: a national cross-sectional survey

BackgroundThe aim was to describe the organisational changes in French EDs in response to the COVID-19 pandemic with regard to architectural constraints and compare with the recommendations of the various...

You Only Traverse Twice: A YOTT Placement, Routing, and Timing Approach for CGRAs

Coarse-grained reconfigurable architecture (CGRA) mapping involves three main steps: placement, routing, and timing. The mapping is an NP-complete problem, and a common strategy is to decouple this process into its independent steps. This work focuses on the placement step, and its aim is to propose a technique that is both reasonably fast and leads to high-performance solutions. Furthermore, a near-optimal placement simplifies the following routing and timing steps. Exact solutions cannot find placements in a reasonable execution time as input designs increase in size. Heuristic solutions include meta-heuristics, such as Simulated Annealing (SA) and fast and straightforward greedy heuristics based on graph traversal. However, as these approaches are probabilistic and have a large design space, it is not easy to provide both run-time efficiency and good solution quality. We propose a graph traversal heuristic that provides the best of both: high-quality placements similar to SA and the execution time of graph traversal approaches. Our placement introduces novel ideas based on “you only traverse twice” (YOTT) approach that performs a two-step graph traversal. The first traversal generates annotated data to guide the second step, which greedily performs the placement, node per node, aided by the annotated data and target architecture constraints. We introduce three new concepts to implement this technique: I/O and reconvergence annotation, degree matching, and look-ahead placement. Our analysis of this approach explores the placement execution time/quality trade-offs. We point out insights on how to analyze graph properties during dataflow mapping. Our results show that YOTT is 60.6 , 9.7 , and 2.3 faster than a high-quality SA, bounding box SA VPR, and multi-single traversal placements, respectively. Furthermore, YOTT reduces the average wire length and the maximal FIFO size (additional timing requirement on CGRAs) to avoid delay mismatches in fully pipelined architectures.

Models of heterogeneous dopamine signaling in an insect learning and memory center.

The Drosophila mushroom body exhibits dopamine dependent synaptic plasticity that underlies the acquisition of associative memories. Recordings of dopamine neurons in this system have identified signals related to external reinforcement such as reward and punishment. However, other factors including locomotion, novelty, reward expectation, and internal state have also recently been shown to modulate dopamine neurons. This heterogeneity is at odds with typical modeling approaches in which these neurons are assumed to encode a global, scalar error signal. How is dopamine dependent plasticity coordinated in the presence of such heterogeneity? We develop a modeling approach that infers a pattern of dopamine activity sufficient to solve defined behavioral tasks, given architectural constraints informed by knowledge of mushroom body circuitry. Model dopamine neurons exhibit diverse tuning to task parameters while nonetheless producing coherent learned behaviors. Notably, reward prediction error emerges as a mode of population activity distributed across these neurons. Our results provide a mechanistic framework that accounts for the heterogeneity of dopamine activity during learning and behavior.

End to end secure e-voting using blockchain & quantum key distribution

A blockchain is a revolutionary computational data structure that enables an open, public, distributed ledger with a wide range of uses. Any new cryptographic application, on the other hand, should take into consideration expected technical improvement during the lifetime of any possibly deployed systems, many of which will be in use for decades. This document addresses the weaknesses of blockchain technology as a result of the development of quantum computers, as well as general recommendations for making blockchain more resistant to such technological breakthroughs. As a result, utilizing a special approach, this work shows many steps of the suggested electronic voting system. The method contains the idea of electronic voting using Quantum key distribution and blockchain security. Explicitly an extended version of the blockchain-based e-voting system to several networks applications. This work also describes the architecture, design, and design constraints of such a voting system in our society with implementation implications.

Structural Assessment Considering Architectural Constraints with Seismic Retrofitting

The Kingdom of Saudi Arabia is located in a low to medium earthquake zone. Therefore, the inclusion of seismic loads in building design was limited to specific building structures such as highrise and midrise in the past decades. Recently, the development and adoption of the Saudi Building Code (SBC) and the experienced seismic activity at many regions in the Kingdom necessitate detailed seismic design considerations for all buildings. Given this, the current work initially emphasizes assessing structural grids obtained from an architectural plan for an existing building in AL Madina. Then the structure has been analyzed critically in such a way to reduce columns and simplify the structural grid. Also, the orientation of columns has been modified to obtain structure symmetry keeping in view the architectural constraints. Two cases have been developed initially: flat slab and solid slab and designed to withstand gravity loads using Saudi Building Provisions. These cases are analyzed for the seismicity of the Medina Region. Since Medina is less prone to seismicity, the building withstands the lateral load calculated based on static analysis. To assess these buildings for stronger earthquakes, we increased the applied load to assess their capacity. Since both the proposed cases fail to withstand the increased seismic load, a bracing system has been introduced at the locations where it does not disturb the architecture of the building. It was observed that introducing bracing improves the performance of the structures. Therefore concluding that complex structural grids schemes can be simplified, regularized, and economized as well. In addition, bracings provide an easy technique to retrofit already existing RC buildings.

A Method to Visualize the Relationship between Regulations and Architectural Constraints

AbstractThe increasing influence of technologies like IoT and AI has made “regulation by architecture” an important discussion point. While system architecture needs to address legal regulations, it also acts as a constraint on stakeholders. Architectural constraints do not require the subject to be aware of them and automatically enforce by preempting behavior. This feature leads to efficient governance, but previous research pointed out concerns caused by the “Unnecessity of Awareness” of architecture. This concern should be avoided by visualizing architectural constraints. However, a concrete visualization method has not been proposed.We propose a method to visualize the relationship between regulations and architectural constraints in accordance with ISO/IEC/IEEE42010:2011. System engineers use this method to reveal the constraints faced by users owing to the architecture and verify that there is no deviation from the regulations.We interviewed legal and engineering experts and concluded that the proposed method is effective under certain conditions.

Resource-aware fluid scheduling with time constraints for clustered many-core architectures

With the rise of many-core processors, real-time applications processing obtains better performance acceleration and parallelization freedom. A validate schedule is able to minimize system resource consumption under the time constraints, which has become a focus recently. This paper establishes an accurate fluid task model and an optimal integer linear programming (ILP) model further. These models not only realize the flexible parallel scheduling, but also achieve co-scheduling between computing and communication resources. Moreover, a heuristic algorithm is presented to generate near-optimal solutions within polynomial time. The experimental results show that the proposed approach is validate and capable to balance the time and resource consumption effectively. It leads the improvement of schedulability and validity up to 68.67% and 24.67% respectively, with 13.16% reduction of the system density averagely.

Visual Concept Reasoning Networks

A split-transform-merge strategy has been broadly used as an architectural constraint in convolutional neural networks for visual recognition tasks. It approximates sparsely connected networks by explicitly defining multiple branches to simultaneously learn representations with different visual concepts or properties. Dependencies or interactions between these representations are typically defined by dense and local operations, however, without any adaptiveness or high-level reasoning. In this work, we propose to exploit this strategy and combine it with our Visual Concept Reasoning Networks (VCRNet) to enable reasoning between high-level visual concepts. We associate each branch with a visual concept and derive a compact concept state by selecting a few local descriptors through an attention module. These concept states are then updated by graph-based interaction and used to adaptively modulate the local descriptors. We describe our proposed model by split-transform-attend-interact-modulate-merge stages, which are implemented by opting for a highly modularized architecture. Extensive experiments on visual recognition tasks such as image classification, semantic segmentation, object detection, scene recognition, and action recognition show that our proposed model, VCRNet, consistently improves the performance by increasing the number of parameters by less than 1%.

A tool for computer-generated dimensioned floorplans based on given adjacencies

In this paper, we present GPLAN, a software aimed at constructing dimensioned floorplan layouts using graph-theoretical and optimization techniques. For GPLAN, the adjacency requirements are given in the following two forms:i.An adjacency graph: It allow users to draw an adjacency graph on a GUI (graphical user interface) corresponding to which GPLAN produces a set of dimensioned floorplans with a rectangular boundary, where each floorplan is topologically distinct from others.ii.A dimensionless layout: Here, users/designers can draw any layout with a rectangular or a non-rectangular boundary on a GUI and GPLAN transforms it into a dimensioned floorplan while preserving the adjacencies, positions, shapes of the rooms.The above approaches represent different ways of inserting adjacencies and GPLAN generate dimensioned floorplans corresponding to the given adjacencies. The larger aim of this work is to provide alternative platforms to users/designers for producing dimensioned floorplans for all given (architectural) constraints, which can be further refined by architects.

A physical and chemical sedimentary record of Laramide tectonic shifts in the Cretaceous-Paleogene San Juan Basin, New Mexico, USA

Fluvial siliciclastic rocks bracketing the Cretaceous-Paleogene (K-Pg) boundary in the San Juan Basin, New Mexico (USA), provide records of regional fluvial and tectonic evolution during the Laramide orogeny. Petrographic analyses of sandstones from the Upper Cretaceous Fruitland Formation and Kirtland Formation and the Paleocene Ojo Alamo Sandstone and Nacimiento Formation show that the rivers depositing these sediments were sourced in areas where unroofing of crystalline basement rocks took place, introducing an increasing proportion of immature detrital grains into the fluvial system through time. After the Cretaceous-Paleogene boundary, rivers deposited an increasing amount of microcline and orthoclase feldspar relative to plagioclase feldspar, suggesting a growing source in unique crystalline basement rocks. Geochemical analyses show significant differences between Al- and K-poor Upper Cretaceous sandstones and Al- and K-rich lower Paleocene sandstones in the San Juan Basin. The high proportion of sand-sized material in the Ojo Alamo Sandstone suggests that it was deposited in a basin with a low ratio of sediment supply to accommodation. However, magnetostratigraphic age constraints suggest it had a relatively high sedimentation and/or subsidence rate of as much as 0.38 m/k.y. The sediment supply must have been high in order to deposit a basin-wide coarse sand-dominated package, suggesting rapid creation of topographic relief in the San Juan uplift, the proposed source area of the Ojo Alamo fluvial system. The observed sedimentary architecture and age constraints of the Ojo Alamo Sandstone, including kilometers-wide sand bodies and limited overbank mudstones throughout most of the outcrop area, are difficult to reconcile with accepted models of aggradation and avulsion in large fluvial systems, but available age and lithologic data make difficult a complete understanding of Paleocene San Juan Basin fluvial systems and basin evolution. Here, we present new lithologic, petrographic, and thickness data from San Juan Basin K-Pg fluvial siliciclastic units and interpretations of their origins.

Structural variation affecting DNA backbone interactions underlies adaptation of B3 DNA binding domains to constraints imposed by protein architecture.

Functional and architectural diversification of transcription factor families has played a central role in the independent evolution of complex development in plants and animals. Here, we investigate the role of architectural constraints on evolution of B3 DNA binding domains that regulate plant embryogenesis. B3 domains of ABI3, FUS3, LEC2 and VAL1 proteins recognize the same cis-element. Complex architectures of ABI3 and VAL1 integrate cis-element recognition with other signals, whereas LEC2 and FUS3 have reduced architectures conducive to roles as pioneer activators. In yeast and plant in vivo assays, B3 domain functions correlate with architectural complexity of the parent transcription factor rather than phylogenetic relatedness. In a complex architecture, attenuated ABI3-B3 and VAL1-B3 activities enable integration of cis-element recognition with hormone signaling, whereas hyper-active LEC2-B3 and FUS3-B3 over-ride hormonal control. Three clade-specific amino acid substitutions (β4-triad) implicated in interactions with the DNA backbone account for divergence of LEC2-B3 and ABI3-B3. We find a striking correlation between differences in in vitro DNA binding affinity and in vivo activities of B3 domains in plants and yeast. Our results highlight the role of DNA backbone interactions that preserve DNA sequence specificity in adaptation of B3 domains to functional constraints associated with domain architecture.

Non‐Volatile Electrolyte‐Gated Transistors Based on Graphdiyne/MoS2 with Robust Stability for Low‐Power Neuromorphic Computing and Logic‐In‐Memory

AbstractArtificial synapses are the key building blocks for low‐power neuromorphic computing that can go beyond the constraints of von Neumann architecture. In comparison with two‐terminal memristors and three‐terminal transistors with filament‐formation and charge‐trapping mechanisms, emerging electrolyte‐gated transistors (EGTs) have been demonstrated as a promising candidate for neuromorphic applications due to their prominent analog switching performance. Here, a novel graphdiyne (GDY)/MoS2‐based EGT is proposed, where an ion‐storage layer (GDY) is adopted to EGTs for the first time. Benefitting from this Li‐ion‐storage layer, the GDY/MoS2‐based EGT features a robust stability (variation < 1% for over 2000 cycles), an ultralow energy consumption (50 aJ µm−2), and long retention characteristics (>104 s). In addition, a quasi‐linear conductance update with low noise (1.3%), an ultrahigh Gmax/Gmin ratio (103), and an ultralow readout conductance (<10 nS) have been demonstrated by this device, enabling the implementation of the neuromorphic computing with near‐ideal accuracies. Moreover, the non‐volatile characteristics of the GDY/MoS2‐based EGT enable it to demonstrate logic‐in‐memory functions, which can execute logic processing and store logic results in a single device. These results highlight the potential of the GDY/MoS2‐based EGT for next‐generation low‐power electronics beyond von Neumann architecture.

Choreographing endo-lysosomal Ca2+ throughout the life of a phagosome

The emergence of endo-lysosomes as ubiquitous Ca2+ stores with their unique cohort of channels has resulted in their being implicated in a growing number of processes in an ever-increasing number of cell types. The architectural and regulatory constraints of these acidic Ca2+ stores distinguishes them from other larger Ca2+ sources such as the ER and influx across the plasma membrane. In view of recent advances in the understanding of the modes of operation, we discuss phagocytosis as a template for how endo-lysosomal Ca2+ signals (generated via TPC and TRPML channels) can be integrated in multiple sophisticated ways into biological processes. Phagocytosis illustrates how different endo-lysosomal Ca2+ signals drive different phases of a process, and how these can be altered by disease or infection.

A daylight-oriented multi-objective optimisation of complex fenestration systems

Complex fenestration systems (CFS) are effective daylighting strategies that improve daylight performance in indoor living spaces. Nevertheless, the design of CFS is complex as it requires specialised knowledge in optical physics and advanced building simulation. This paper presents an evaluation method (CFStrace) to optimise the CFS design in a multi-objective optimisation setting. The method takes into account both architectural and environmental conditions that maximise the effect of light redirection for complex fenestration systems to its full potential. The research aims to demonstrate a multi-objective and multi-scenario optimisation methodology for designing complex fenestration systems. The parameters of the optimisation problem can be easily changed due to the parametric nature of the modelling environment used. Thus, this gives designers the flexibility to adjust the CFS parameters and decrease their discretisation. To support the presented methodology, a case study is presented to demonstrate the design process and guide designers in selecting the best design option. The case study involves the design optimisation of a sinewave-shaped light redirecting panel by tweaking its geometrical parameters and comparing the optimised result with existing light redirecting panels. The case study results indicate that optimising a CFS according to the architectural design can improve daylight metrics (such as improving the useful daylight illuminance (UDI) by +10%). The case study reveals the importance of addressing architectural and environmental constraints when designing CFS as the optimised design can differ with changing parameters such as the room depth or panel height.