Design Decisions Research Articles

Passive Energy Conservation Strategies for Mitigating Energy Consumption and Reducing CO2 Emissions in Traditional Dwellings of Peking Area, China

Within China, brick dwellings stand as archetypal relics of traditional habitation, embodying a “living fossil” status. The sustainability of these dwellings is contingent upon the integration of energy-conservation strategies. This study scrutinized and empirically assessed a representative dwelling in the Peking area. Using numerical simulations, the impact on energy consumption of factors such as insulation and glazing type, external wall thickness, insulation thickness, and solar energy utilization was evaluated. The outcomes reveal that introducing external thermal insulation—specifically, expanded polystyrene panels with a thickness of 60 mm and 40 mm for the roof and exterior walls, respectively—along with a sunspace of depth 1.5 m yielded superior energy efficiency. Additionally, substituting conventional roofing with solar tiles exhibited a potential annual electricity generation coupled with an annual solar radiation conversion efficiency of 17%. Collectively, these strategies induced a substantial reduction in annual energy consumption. This study presents tailored energy-conservation measures and provides design decision support for architects’ practical recommendations on thermal environment control of passive traditional dwellings in the Peking area.

Innovations in Software Configuration: Introducing a Data Comparison Tool Based on the Myers Diff Algorithm

In the realm of software project development, it's not uncommon for changes to emerge at various stages of a project's lifecycle. Such alterations can manifest in virtually every facet of the software development process, from conceptual design decisions down to the minutiae of the source code. To proficiently manage and track these dynamic changes, professionals turn to a specialized toolset known as Software Configuration Management (SCM). One of the standout features that SCM tools bring to the table is the 'diff' capability. This functionality allows developers to identify and review the disparities between two versions of source code. Recognizing the importance and utility of this feature, the primary objective of this research is to create an advanced diff application. This application, by leveraging the Myers Diff algorithm, is meticulously designed to pinpoint and showcase differences in characters between two sets of text-based data. Moreover, it accentuates these differences by visually highlighting the contrasting characters between the two datasets. To ensure the reliability and accuracy of this newly developed tool, we undertook a series of validation tests. We juxtaposed the results from our application against those from a comparable existing tool. Impressively, the discrepancies in results were minimal, with a marginal difference of just 1%. This suggests not only the utility but also the precision of our application in real-world software development scenarios.

Integrating Aerial and 3D Data into a Data-Driven Decision-Making Workflow for Nature-Based Stormwater Solutions

Urbanization and climate change have increased the need for stormwater management and nature-based solutions. Decisions made at the project level impact the emergence of the systemic traits of the stormwater network and the functionality of the catchment areas in urban planning. To that end, it is vital to introduce the decision-making tools for analysing both the utilities and amenities of nature-based solutions (NBS) to increase their adoption to reduce the peak loads in the stormwater system and, to that end, mitigate the impacts of climate change. There is a deficiency in employing a software-based approach to analyse the qualitative and quantitative aspects of NBSs to back up design decisions. This paper demonstrates a workflow using drone-based photogrammetry, 3D modelling, and simulation software to generate visual and functional models assisting in informed decision-making in the design of stormwater systems as functional landscape architecture. Using aerial data from drones and modelled design solutions, the proposed workflow simulates rain events, infiltration, evaporation, water flow, and the accumulation of stormwater in a way that allows the visual and quantified analysis of detailed landscape architecture designs. The paper provides an example of a rooftop site simulation demonstrating the infiltration and flow of water to the drainage. The visual decision-making method provided can aid in investment decisions for functional landscape design in support of stormwater management.

A Design Vocabulary for Data Physicalization

Although physical artifacts that represent data have been used for centuries, the research field—known as data physicalization—has only recently gained traction. Compared to data visualization, there is no established vocabulary for analyzing and discussing the properties of physicalizations. Through a grounded analysis of examples and literature, we propose a comprehensive design vocabulary, which consist of three separate, but connected parts: explicit variables , implicit properties , and consequential aspects . Explicit variables build on visual variables known from visualization and extend it to account for physicalization’s multi-modal nature. Implicit properties concern elements which are central to the design intention and user experience of physicalizations, yet are not a result of “explicit” encoding strategies. Finally, consequential aspects refer to unintentional effects of design decisions, that influence how a physicalization is experienced. Our work illustrates how physicalizations incorporate opportunities and challenges that are not afforded in other data representations, such as embodiment and imagined touch . With this, we contribute to generating theory on physicalization. Our design vocabulary can support (1) creators through informing their design processes and highlighting design strategies, (2) educators, and (3) academics and practitioners to analyse existing physicalizations, and reflect on the impact of design decisions on interpretation and experience.

Question Dosage in MOOCs

Video lectures in online courses often use pop-up questions or quizzes to enhance learners’ engagement and their learning outcomes. However, there is limited research about how frequently pop-up questions should be asked, considering how this design decision may impact learners’ self-regulation and motivation to learn, as well as their perceptions of confidence and challenge associated with the learning content. This study aims to answer the above questions while considering learners’ final learning outcomes in a massive open online course (MOOC). In this study, learners were divided into high and low frequency groups. The high frequency group were given a question almost every 2 minutes whereas the low frequency group were given a question only once at the end of the video. No significant differences on any of the above factors were found between the two groups. Educators may take these results into account when designing MOOCs in the future. MOOCs are costly and time-consuming to create, and this experiment suggests that using resources on this level of detail may not be necessary.

Evaluating the Public Climate School, a multi-component school-based program to promote climate awareness and action in students: A cluster-controlled pilot study

IntroductionDespite the potential of school-based programs targeting climate awareness and action to support students in addressing the climate crisis and to improve their mental health and well-being, there is limited evidence for their effectiveness. In preparation for a cluster-randomized controlled trial, we assessed the feasibility of evaluating the Public Climate School (PCS), a one-week school program in Germany, and its effects on theory-based behavioral and psychological outcomes. Material and methodsWe enrolled 158 students from 11 classes (grades 7–13) into a cluster-controlled pilot study. Four classes were allocated to the waitlist control group and 7 to the intervention group participating in the PCS in November 2021. Using online surveys, we assessed theory-based behavioral and psychological outcomes at baseline and follow-up. Two-level models were used to investigate changes in outcomes. Results125 students completed the baseline and follow-up survey (dropout rate: 21 %). For most outcomes we observed no between-group differences, except for pro-environmental communication and engagement (e.g., posting on social media; p=.040) and perceptions of environmental norms (p=.001) in the anticipated direction. ConclusionThis study confirmed the feasibility of evaluating the PCS and provides parameter estimates to guide sample size calculations and study design decisions for future research. Together with recent work on the association between collective action and mental health, the effect of the PCS on pro-environmental communication and engagement highlights the value of examining effects of education for sustainable development programs on student health and linking them to collective action in future work.

Optimizing thermal comfort in physical exercise spaces: A study of spatial and thermal factors

Fitness centers have become famous for maintaining a healthy lifestyle. They require different thermal comfort conditions and higher fresh air supply rates than other indoor spaces. However, even well-designed centers may cause discomfort due to factors such as design decisions, ventilation, overheating, and overcrowding. The standards for fitness centers do not consider these specific requirements sufficiently, so this study focuses on understanding the thermal comfort requirements during physical exercise and evaluating spatial and thermal factors affecting the thermal environment around the body. The study investigated the ceiling height, lateral and frontal distances between machines, and vent locations as spatial factors and inlet temperature and air velocity as thermal factors. A thirty-minute moderate-intensity constant work rate exercise test was conducted in a controlled climatic chamber using a cycle ergometer with six healthy male participants. The experiment conditions were simulated in CFD software using the collected data. Once a validated simulation model was provided, computational models for different environmental and spatial scenarios for the five-person cycling class were generated. Using Taguchi L9 (34) orthogonal arrays method, nine spatial scenarios were simulated with three different thermal operations each. Optimal factor levels were determined by using thermal comfort conditions (based on predicted mean vote) around the body’s thermal plume. The results showed that a ceiling height of 5 m, lateral and frontal distances of 1 m and 0.5 m between machines, and Type 2 (two inlets mounted on the ceiling) ventilation strategy were optimal for achieving better thermal comfort values in a thermal condition of 18 °C and 0.2 m·s−1. The study found that increasing the ceiling height and using cross-positioned vents that project air vertically from the ceiling improved the comfort conditions significantly. It is expected that these criteria, which were determined, compared with the standards and detailed, will contribute to the production processes of comfortable exercise spaces.

ON THE POTENTIAL OF USING PHENOMENOLOGICAL METHODS IN THE RESEARCH OF BARRIER SITUATIONS IN UNIVERSAL DESIGN

The article is focused on the study of individuals' perception of (exclusive) objects in the environment. The paper also describes the potential of extrapolating the phenomenological method to the field of design science, since design is perceived as a social and intersubjective process. The article proposes the idea that phenomenological methodology, unlike analytical methodology, (focuses on the study of) the "causes", the meanings of the design object and also explores the meaning-producing constructions that influence the formation of the object in the process of its emergence. This article suggests that by studying the contextual history of the process of creating a certain universal design object, rather than the finished (completed) object, it is possible to identify the meaning-producing factors, characteristic contextual features of the social (or physical) environment that influenced a particular designer's decision at different stages of the design process. Phenomenological methods have the potential to become a valuable tool for researching the phenomena of universal design, in particular for the analysis of barrier situations.

Don’t let perfect be the enemy of good: how perfectionism influences human-centred designing engagement and communal design production in civil engineering

Perfectionism is a personality trait associated with a desire for flawlessness, high-standard expectations and criticism of the self and others. As engineering design seeks to address more wicked problems that move beyond technical considerations, it is possible that engineers with perfectionism may struggle to engage flexibly with complexity and more creativity-focused solutions. The present study seeks to understand perfectionism prevalence in an undergraduate cohort of civil engineers and the impact of this trait on complex design decisions and engagements that include social as well as technical considerations. 184 civil engineering students were involved in this study. We found that 74.5% of the engineers classify as perfectionists, with 68.5% of these perfectionists being maladaptive. Further, we examined how perfectionism associated with Communal Designs, a design approach that aims to meet physical community needs as well as more metaphysical, empathy-informed criteria. We found that although perfectionists were more likely to have higher scores of prosocialness and empathy, non-perfectionists were more likely to produce Communal Designs. This suggested an apparent intention-behaviour mismatch. Engineering students may have intended to but then failed to produce Communal Designs; this could also be explained via our finding that perfectionists tend to have higher social desirability scores. The results indicate that complex decision-making in engineering design cannot be separated from the mindsets and personalities of engineers. Strategies to mitigate the negative impact of perfectionism are discussed, including both supported exposure to open-ended, contextualised design, and the use of critical reflection. A regression model predictive of Communal Design production was also developed and discussed using engineering undergraduates’ personality characteristics’ scores as predictors.

Decoupling awake and asleep thermal comfort: Impact on building design optimization

Researchers suggest that humans have different preferred thermal conditions for asleep and awake periods. Yet, current standards underpinning thermal comfort assessment and energy analysis in buildings are exclusively based on awake comfort preferences and do not differentiate between awake and asleep conditions. This study hypothesizes that considering sleep thermal comfort in building performance modeling would significantly impact the energy and comfort performance of building design options and, thus, impact design decisions optimized for these goals. No prior studies have been found to test this hypothesis. A review of research on sleep thermal comfort is conducted to find suggested optimal temperatures for sleeping. Then, the impacts of applying sleep thermal comfort ranges on optimal residential building design decisions were analyzed through a simulation-based analysis. A multi-objective optimization model was developed, first, with standard comfort ranges at all times, and second, with sleep and standard comfort ranges at appropriate hours. Both optimal and non-optimal solutions were analyzed in terms of energy consumption and thermal comfort. The results demonstrated that the design of optimal buildings differs significantly when including sleep thermal comfort (e.g., more window-shading proved to be a more energy-efficient and comfortable solution than when sleep thermal comfort was ignored.) Therefore, the consideration of sleep thermal comfort impacts building design decisions and provides energy-saving opportunities. This research implies, for the first time, that the simulation-aided design process of high-performance buildings where sleep occurs should consider sleep thermal comfort separately from awake comfort to better inform the decision-making process.

Creating a contact binary via spacecraft impact to near-Earth binary asteroid (350751) 2002 AW

Contact binary asteroids are ubiquitous in the solar system: the Kuiper belt, main belt, and near-Earth populations all house these complex aggregates. Although contact binaries account for up to 30% of small bodies in the solar system, the formation of one has yet to be observed. We present a preliminary mission design to create a contact binary asteroid and observe its formation using a binary NEO system, a kinetic impactor, and an observer spacecraft. Not only does this mission address an important gap in planetary science, it also serves the planetary defense community: it will further demonstrate planetary defense technology to provide unique observation opportunities. A binary system offers a convenient natural laboratory for this mission, as the ability to form a contact binary using a kinetic impactor depends greatly on the size of the target and the proximity to its parent body. From among all known binary near-Earth objects, binary asteroid system (350751) 2002 AW was chosen for this case study. A spacecraft can achieve rendezvous with this system from low-Earth orbit with a cheap total ΔV ≈ 4.3 km/s. A pair of spacecraft launch on the same launch vehicle and separate before asteroid impact. The two spacecraft are (1) an impactor that has been adapted from the DART spacecraft and (2) an observer spacecraft that will rendezvous with the binary system and observe the creation of the contact binary. The spacecraft impact must be designed such that it redirects the secondary into a collision course with the primary while not catastrophically disrupting the target asteroid. Impact parameters such as angle of impact, catastrophic disruption limit, and the β factor have been considered. Among other design decisions, we present our target-selection methodology, launch-vehicle considerations, and launch opportunities.

Implementing dynamic subset sensitivity analysis for early design datasets

Engaging with performance feedback in early building design often involves building a custom parametric model and generating large datasets, which is not always feasible. Alternatively, large parametric datasets of general design problems and filtering methods could be used together to explore specific design decisions. This paper investigates the generalizability of a method that dynamically assesses variable importance and likely influence on performance objectives as a precomputed design space is filtered down. The method first trains linear model trees to predict building performance objectives across a generic design space. Leaf node models are then aggregated to provide feedback on variable importance in different design space regions. This approach is tested on three design problems that vary in number of variables, samples, and design space structure to reveal advantages and potential limitations of the method. Algorithm improvements are proposed, and general recommendations are developed to apply it on future datasets.

A simulation-based evaluation of using PCMs in buildings for energy efficiency under different climate conditions

Today, majority of energy consumed in buildings is used to provide thermal comfort conditions. Reducing heating and cooling loads to provide comfort conditions in buildings is possible by taking the right passive design decisions concerning the variables that affect these loads. The building envelope which seperates indoor environment from the outdoor environment and affects the development of indoor thermal comfort conditions is the most important determining factor for energy loads in buildings. In this study, after applying PCM on the building envelope and inner walls and inner floors annual heating, cooling and total energy consumptions and indoor environment comfort conditions in the zones were evaluated. The study was done for Istanbul representing temperate humid climatic zone and for Diyarbakir representing hot-dry climatic zone in the same degree-day region according to the TS825 standards. The residential building simulated for calculations is a 3 storey building with a rectangle floor plan and flat roof and the dimensions of these buildings are 10 m × 30 m × 9 m. The building comprises 9 zones and the building coverage is 300 m2. In order to reduce the difference in energy consumption and thermal comfort conditions among the zones due to their different locations, PCM was applied on inner walls and inner floors in addition to the building envelope to develop a range of alternatives. Annual energy performance evaluation and calculation of daily operative temperature values for January 21 which represents the heating period and July 21 which represents the cooling period were done by the EnergyPlus simulation tool. According to the calculations, the total energy load of the building in the A4.2 alternative where PCM was applied on the building envelope and on inner walls and inner floors was reduced by 11.96 % and 9.69 % in Istanbul and Diyarbakır respectively. With the alternatives, differences in energy consumption among the zones were reduced but not eliminated. Operative temperature values in the zones changed by 1.04 °C – 3.32 °C in Istanbul and by 0.87 °C – 1.16 °C in Diyarbakır with the PCM application contributing to the improvement of indoor comfort conditions.

A unified approach for evaluating mechanical compression tests for polymer bead foams

AbstractIn the realm of material characterization, the mechanical properties of polymer foams play a pivotal role in shaping their applicability across diverse industries. In this pursuit, we present a novel approach to standardize and automate the assessment of key mechanical parameters for Expanded Polypropylene (EPP) foams using a self‐developed Python script, made freely available for the scientific community. We precisely determine the compression modulus, plateau onset, and onset of densification strain for EPP foams across various densities. The script's effectiveness is demonstrated through comparisons with manual evaluations and established standards, highlighting its superiority, consistency, and suitability for a wide range of materials and conditions. Moreover, the script enables the analysis of energy absorption, shedding light on the intricate relationship between density and energy dissipation. Finally, our approach was extended to other foams to provide insight on their mechanical properties. The automated methodology ensures accuracy, reproducibility, and efficiency, thereby advancing the understanding of foam materials and facilitating informed design decisions. This research contributes to laying a foundation for the standardized assessment of foam mechanical properties, which could potentially facilitate their effective use in other applications.

Open-Loop Control Co-Design of Semisubmersible Floating Offshore Wind Turbines Using Linear Parameter-Varying Models

Abstract This paper discusses a framework to design elements of the plant and control systems for floating offshore wind turbines in an integrated manner using linear parameter-varying models. Multiple linearized models derived from aero-elastic simulation software in different operating regions characterized by the incoming wind speed are combined to construct an approximate low-fidelity model of the system. The combined model is then used to generate open-loop, optimal control trajectories as part of a nested control co-design strategy that explores the system’s power production and stability using the platform pitch tilt as a proxy in the context of crucial plant and control design decisions. The radial distance between the central and outer columns and the diameter of the outer columns of the semisubmersible platform are the plant design variables. The platform stability and power production are studied for different plant design decisions. The effect of plant decisions on subsequent power production and stability response of the floating wind turbine is quantified in terms of the levelized cost of energy. The results show that the inner-loop constraints and the plant design decisions affect the turbine’s power and, subsequently, the cost of the system.

Multidisciplinary Optimization of Thermodynamic Cycles for Large-Scale Heat Pumps With Simultaneous Component Design

Abstract The performance of high temperature heat pumps (HTHPs) is highly dependent on the efficiency of its main components, which need to be optimally matched especially in closed cycles. The design process is therefore a challenging task as many disciplines and varying modeling depths need to be considered. Consequently, this is usually a sequential procedure beginning with cycle definition and raising the fidelity for component design. Fundamental design decisions are made based on assumptions for component performance. Mistakes in the phase of cycle definition are hard to reverse in later design stages. Therefore, this work introduces holistic approaches to the multidisciplinary design of closed Brayton cycles. Aerodynamic compressor design with two-dimensional throughflow analysis and geometry-based heat exchanger sizing are simultaneously optimized with thermodynamic cycle parameters. The presented methodologies make use of highly sophisticated design tools drawing on many years of experience in gas turbine design. The results demonstrate that holistic heat pump optimization can be successfully performed with reasonable computational effort. The advantages compared to conventional sequential design are elaborated. A comparison of two optimization concepts indicates that splitting up the design vectors of cycle and components shows the tendency to improve robustness. Finally, the tradeoff between system compactness and performance is demonstrated with a multi-objective optimization study.

Seasonal analysis of land surface temperature using local climate zones in peak forest basin topography: A case study of Guilin

Understanding the characteristics of Land Surface Temperature (LST) is crucial to mitigate the Surface Urban Heat Island (SUHI) effect. Local Climate Zones (LCZs) framework can be applied in LST analysis and SUHI quantification. However, this framework primarily focuses on evaluating detailed local-scale SUHI, thereby failing to provide a comprehensive assessment of the overarching SUHI trends at the urban level. Additionally, existing LST analyses ignored geographic factors, resulting in partial analysis of LST, especially in areas with complex geography. To fill these gaps, the study develops a SUHI assessment method combining an improved surface urban heat intensity ratio index with LCZs-based SUHII, enabling a dual evaluation of both overall and detailed SUHI effect. The impact of geographic factors, both topography and natural features, on seasonal LST patterns is investigated, especially within built LCZs. Additionally, the spatio-temporal image fusion model is employed to address issues of cloud effects or image mutilations in LST results. Guilin, with unique peak forest basin topography, is selected as a case study to represent complex geographical areas. The results reveal the following: (1) An abnormal heat island phenomenon occurs during winter due to Guilin's distinctive geomorphological conditions. (2) Cooling effects influenced by mountains and water bodies on different built LCZs exhibit seasonal variation, with the strongest cooling effect observed within a 50-m distance. LCZ 2 consistently exhibits the strongest cooling effect. The study offers valuable insights for guiding decisions in sustainable urban planning and design, especially in cities influenced by complex local geography.

Which design decisions in AI-enabled mobile applications contribute to greener AI?

Which design decisions in AI-enabled mobile applications contribute to greener AI?

Hits and misses in the last decade of open science: Researchers from different subfields and career stages offer personal reflections and suggestions

The success of Open Science in addressing the replication crisis and restoring credibility in psychology can be understood more completely by examining the successes and challenges of adapting the recommended best practices by researchers at different types of institutions, different career stages, and from different subfields within social and personality psychology. In this article, we offer personal reflections about the impact and future of the Open Science movement in a conversational form between three researchers at varying career stages who focus on different subdisciplines (relationship science, diversity science, and social neuroscience and social cognition) and work at universities that place a different emphasis on research (relative to teaching and service). We see many successes of the open science movement, but we also note that implementation has trailed behind its full potential because (a) the incentive structures of our existing rigid system remain misaligned with some open-science goals, and (b) some open science solutions were designed by researchers with certain types of scientific practices in mind. We all feel encouraged by the focus on larger samples, greater data sharing, and pre-registration both for experimental design and analytical decisions. However, there are areas that need attention. Our perspective is that the open science movement has not been as strong of an ally as it could be to another goal of psychological science: increasing diversity, equity, and inclusion. Additionally, more careful consideration of how to facilitate data sharing and pre-registration is needed and may necessitate a shift in the incentive structure of our field.

Species delimitation with limited sampling: An example from rare trapdoor spider genus Cyclocosmia (Mygalomorphae, Halonoproctidae).

The outcome of species delimitation depends on many factors, including conceptual framework, study design, data availability, methodology employed and subjective decision making. Obtaining sufficient taxon sampling in endangered or rare taxa might be difficult, particularly when non-lethal tissue collection cannot be utilized. The need to avoid overexploitation of the natural populations may thus limit methodological framework available for downstream data analyses and bias the results. We test species boundaries in rare North American trapdoor spider genus Cyclocosmia Ausserer (1871) inhabiting the Southern Coastal Plain biodiversity hotspot with the use of genomic data and two multispecies coalescent model methods. We evaluate the performance of each methodology within a limited sampling framework. To mitigate the risk of species over splitting, common in taxa with highly structured populations, we subsequently implement a species validation step via genealogical diversification index (gdi), which accounts for both genetic isolation and gene flow. We delimited eight geographically restricted lineages within sampled North American Cyclocosmia, suggesting that major river drainages in the region are likely barriers to dispersal. Our results suggest that utilizing BPP in the species discovery step might be a good option for datasets comprising hundreds of loci, but fewer individuals, which may be a common scenario for rare taxa. However, we also show that such results should be validated via gdi, in order to avoid over splitting.