Evaluation Of Design Alternatives Research Articles

Advanced UAV Design Optimization Through Deep Learning-Based Surrogate Models

The conceptual design of unmanned aerial vehicles (UAVs) presents significant multidisciplinary challenges requiring the optimization of aerodynamic and structural performance, stealth, and propulsion efficiency. This work addresses these challenges by integrating deep neural networks with a multiobjective genetic algorithm to optimize UAV configurations. The proposed framework enables a comprehensive evaluation of design alternatives by estimating key performance metrics required for different operational requirements. The design process resulted in a significant improvement in computational time over traditional methods by more than three orders of magnitude. The findings illustrate the framework’s capability to optimize UAV designs for a variety of mission scenarios, including specialized tasks such as intelligence, surveillance, and reconnaissance (ISR), combat air patrol (CAP), and Suppression of Enemy Air Defenses (SEAD). This flexibility and adaptability was demonstrated through a case study, showcasing the method’s effectiveness in tailoring UAV configurations to meet specific operational requirements while balancing trade-offs between aerodynamic efficiency, stealth, and structural weight. Additionally, these results underscore the transformative impact of integrating AI into the early stages of the design process, facilitating rapid prototyping and innovation in aerospace engineering. Consequently, the current work demonstrates the potential of AI-driven optimization to revolutionize UAV design by providing a robust and effective tool for solving complex engineering problems.

A Generative Design Approach to Improving the Environmental Performance of Educational Buildings in Hot Arid Climates. (Assiut National University as a Case Study)

The architectural design process is complex, involving diverse objectives that may be contradictory, and on which orientation exerts significant influence. The artificial intelligence application, Generative Design facilitates solving multi-objective design dilemmas through the creation and evaluation of numerous design alternatives. However, its exploration in educational buildings in hot arid climates remains limited. Given the impact of spaces’ function distribution, this study aims to optimize it in the typical plans of educational buildings. Employing a multi-objective design approach to enhance environmental performance. The study is conducted and evaluated in national universities in Egypt as a case study, specifically in Assiut City. The results revealed that the optimum design for a certain objective has not equated to optimal performance for other goals, highlighting an inherent contradiction between them. Among 26,334 possible alternatives for spaces’ function distribution, the difference between the optimal scenario and the least favourable one is significant for the parameters related to study spaces: natural daylighting, and visual comfort, ranging from 10% to 24%, besides around 1% difference for parameters related to the whole building, including energy consumption, thermal comfort, and carbon emission. This research offers a framework applicable to various building types. Additionally, it encourages decision-makers to adopt a no-cost sustainable design approach.

Product design evaluation based on improved CRITIC and Comprehensive Cloud-TOPSIS – Applied to automotive styling design evaluation

To tackle the challenge of achieving more reasonably calculation of evaluation indicator weights and a more scientifically rigorous scoring system for ranking in product design evaluation, a novel evaluation model that leverages improved CRITIC (Criteria Improved Criteria Importance) and CC-TOPSIS (Comprehensive Cloud-Technique for Order Preference by Similarity to Ideal Solution) is proposed. Firstly, the process commences with the collection of qualitative product evaluations from respondents through questionnaires, presented in the form of fuzzy confidence intervals. Subsequently, these evaluations are transformed into generalized trapezoidal fuzzy numbers, and their center of gravity values are calculated. Secondly, after the weight for each evaluation indicator is calculated employing an enhanced CRITIC approach, a weight cloud model utilizing the backward cloud methodology is constructed. Subsequently, the scoring cloud model is generated as a backward cloud, followed by the application of an enhanced synthesis operator to amalgamate the weight cloud model with the scoring cloud model, culminating in the formation of a comprehensive cloud model. Finally, the product design schemes are ranked using the Cloud-TOPSIS method, and a cloud chart analysis provides insights into optimization directions. The utilization of this methodology in assessing automotive styling design serves as a compelling showcase of its practicality and efficiency, in addition to, the method's resilience is further bolstered through a sensitivity analysis of the evaluation indicators. This method adeptly computes the weights of evaluation indicators, while also addressing the inherent variability in weight values and incorporates the benefits of Cloud Model and TOPSIS in the evaluation of product design alternatives, ultimately elevating the rationality and the scientific underpinnings of the product design evaluation process.

Eco-performance evaluation of product designs – an integrated fuzzy complex proportional assessment with life cycle assessment

ABSTRACT The growing public awareness has driven enterprises to develop environmentally friendly designs to fulfill customer satisfaction. Some eco-design tools have been introduced to designers to support greener product design and development qualitatively. However, most require qualitative judgement during the evaluation process. Although life cycle assessment (LCA) helps quantify a product system’s environmental loads, it requires much time and resources for data collection. Design selections are not preferred during the early product development stage, especially when the product development schedule is rather tight nowadays. This paper proposes a practical approach integrating a fast-track LCA, fuzzy-set, with COmplex PRoportional ASsessment (COPRAS). This paper proposes an approach by incorporating the fuzzy-set, COPRAS, and LCA for decision-makers to evaluate design alternatives at the early product development stage. The originality of the paper is to provide an efficient approach to evaluating various design alternatives by quantifying their corresponding environmental burdens using LCA and fuzzy-set. Three distinct features can be found in the proposed generic approach. This study brings two contributions to the related field. For the area related to environmental impact assessment, this study illustrates the applicability of LCA in conjunction with COPRAS and fuzzy-set for the design alternative selection. Decision-makers can apply the proposed method that in-depth knowledge of environmental impact assessment is not essential, and the qualitative input required is minimal compared to a comprehensive LCA study.

Security Risk Assessments: Modeling and Risk Level Propagation

Security risk assessment is an important task in systems engineering. It is used to derive security requirements for a secure system design and to evaluate design alternatives as well as vulnerabilities. Security risk assessment is also a complex and interdisciplinary task, where experts from the application domain and the security domain have to collaborate and understand each other. Automated and tool-supported approaches are desired to help manage the complexity. However, the models used for system engineering usually focus on functional behavior and lack security-related aspects. Therefore, we present our modeling approach that alleviates communication between the involved experts and features steps of computer-aided modeling to achieve consistency and avoid omission errors. We demonstrate our approach with an example. We also describe how to model impact rating and attack feasibility estimation in a modular fashion, along with the propagation and aggregation of these estimations through the model. As a result, experts can make local decisions or changes in the model, which in turn provides the impact of these decisions or changes on the overall risk profile. Finally, we discuss the advantages of our model-based method.

Embedding Acoustic Analysis in Landscape Architecture Design Processes: A Case Study of Munich Airport

Noise is the number two environmental health risk in Europe. With the majority of the world’s inhabitants residing in ever-growing cities, urban noise impacts an increasing number of people. Urban airports significantly contribute to urban noise, and their spatial effects far exceed their boundaries. While indoor acoustic mitigation in architecture is growingly addressed using parametric tools, there is limited research on mitigating noise with digital means through landscape and urban design. Moreover, there is a lack of methods for ameliorating urban noise through ground-forming. To address this, this paper contributes a novel method for integrating acoustic analysis in parametric landscape-forming. The method includes collecting on-line and on-site noise data, developing alternative landscape formations for mitigating noise, and evaluating design alternatives within a single digital design environment. This method was applied using research by design and examined on a case-study site adjacent to the Munich Airport. Three landform landscape designs for a park are developed, and their acoustic performance is compared. The results indicate the possibility of integrating acoustic considerations in landscape architecture, and the method provides a step-by-step guide for doing so. This capacity also promotes the long-term goal of increasing the environmental performance of urban grounds.

User Interface Evaluation of Design Alternatives of the Emotion-Libras—An Emotional Self-Report Instrument for Sign Language Users

Abstract For researchers interested in analyzing participants’ self-reflection about their emotional experience during user studies, having an instrument designed for a specific target user can be seen to show empathy for providing socio-cultural elements that involved parties feel a connection with. In user studies, communication mediation between sign language users and non-signers may include a bias; therefore, direct communication between the involved parties is welcome to reduce this risk and expand sign language users’ autonomy. This paper presents the Emotion-Libras, a self-report instrument to collect emotional responses of sign language users after interacting with technology and report findings from a user study. We conducted a focus group with five sign language users to collect their perceptions regarding the three design alternatives of the instrument. As a result, participants selected the best-fitted design interface of the instrument and also found room for improvement in video quality, language choice, written labels and user control.

Priming Engineers to Think About Sustainability: Cognitive and Neuro-Cognitive Evidence to Support the Adoption of Green Stormwater Design.

Green infrastructure is the application of nature-based solutions like bioswales, rain gardens, and permeable pavements to reduce flooding in urban areas. These systems are underutilized in the design of the built environment. A barrier to their implementation is that design engineers tend to discount the tangential benefits of these greener systems and overweigh the associated risks. This study tested whether priming engineers to think about the environmental and social sustainability benefits of green infrastructure can influence what attributes engineers consider and how they weigh these attributes during the design decision-making process. Forty engineering students trained in stormwater design were asked to evaluate the implementation of a conventional stormwater design option and a green stormwater design option. Their preferred design option was recorded and the changes in their neuro-cognition were measured using functional near infrared-spectroscopy. Half of the engineers were asked to first consider the potential outcomes of these options on the environment and the surrounding community. Priming engineers to first consider environmental and social sustainability before considering the cost and risk of each option, significantly increased the perceived benefits the engineers believed green infrastructure could provide. The priming intervention also increased the likelihood that engineers would recommend the green infrastructure option. The engineers primed to think about environmental and social sustainability exhibited significantly lower oxy-hemoglobin in their ventrolateral, dorsolateral, and medial prefrontal cortex through multiple phases of the judgment and decision-making process. The intervention appears to increase cognitive representativeness or salience of the benefits for green infrastructure when engineers evaluate design alternatives. This relatively low-cost intervention, asking engineers to consider environmental and social sustainability for each design alternative, can shift engineering decision-making and change neuro-cognition.

Concept selection for the preliminary DTT remote maintenance strategy

Divertor Tokamak Test (DTT) is the next Italian facility for nuclear fusion research aiming at bringing alternative divertor solutions to a sufficient readiness level to be adopted by the European DEMOnstrating fusion power reactor (EU-DEMO). Since a non-negligible activation is expected on plasma-facing components after DTT shutdown, remote maintenance is mandatory. This work deals with the concept selection for the DTT remote maintenance strategy, in the 2019 reference configuration. First, we present the criteria that we have derived for evaluation of design alternatives. Then, we briefly present the design alternatives developed so far for divertor and first wall remote maintenance. With this regards, three alternatives have been developed for divertor remote maintenance and two alternatives have been developed for first wall remote maintenance. The concept selection process is based on the use of ELIGERE, a decision support tool for concept selection based on the Fuzzy Analytical Hierarchy Process. More than 20 experts from several European institutions have been involved in the concept selection process. The work concludes by presenting the results of the concept selection process, in terms of optimal strategies for divertor and first wall remote maintenance.

Generative design to reduce embodied GHG emissions of high-rise buildings

Although countries have reduced their total greenhouse gas emissions by improving energy and transportation policies, the contribution of the building sector has been widely overlooked. Embodied emissions (EE) are particularly important since they are released upfront rather than over building lifespans, making them critical for near-term emission reduction targets. Accordingly, this study developed a tool to reduce EE at the conceptual stage of high-rise residential buildings. The tool combines generative design with goals and constraints inherent to conceptual building design: maximizing site use, views, and building code compliance. In a case study, it was able to achieve a 7% reduction in EE compared to a sub-optimal solution. This research elucidated the potential of using generative design in early-stage design, proposed novel systems for the generation and evaluation of design alternatives, and delivered GenGHG, a ready-to-use, open-source tool for conceptual building design.

Early-stage in silico flowsheet analysis for a monoclonal antibody platform

In silico frameworks have the potential to improve experimentally designed processes for monoclonal antibody (mAb) manufacturing. In this paper, a framework for the analysis of mAb process alternatives is presented with the objective of realizing process improvements from a flowsheet perspective. The key elements of the proposed method include the generation and decomposition of the design space, the formulation of a flowsheet model, and the simulation and evaluation of alternative designs. An example of an evaluation of a new technology step in mAb manufacturing is given to demonstrate the application of the framework and to illustrate how the design problem is solved using the proposed step-by-step procedure. The methodical approach provides the opportunity to systematically and quantitatively evaluate the impact of different design decisions before selecting a final design. Therefore, it supports the finding of improved process designs that may be ignored using conventional experiment-based methods and sequential optimization of processing steps.

D-ART for collaboration in evaluating design alternatives

Evaluating design ideas is an integral part of designing built environments. It involves multiple stakeholders with diverse backgrounds reviewing design solutions by studying their form and performance data. Although there are computational systems for supporting evaluation tasks, they are either highly specialised for designers or configured for a particular workflow with limited functions. We developed a Design Analytics method aiming at a collaborative and data-driven evaluation of alternatives in the design-evaluate-feedback cycle. Adopting this approach, we introduce D-ART as a prototype system composed of customisable Web interfaces for presenting design alternatives, enabling stakeholders to participate in data-informed discourse on alternatives and providing feedback to the design team. Its system design considers requirements gathered through literature review, critical analysis of the existing systems and collaboration with our industry partners. Finally, we assessed D-ART’s design through an expert review evaluation, which generally reported positive results on the system’s goals.

Graph-based algorithmic design and decision-making framework for district heating and cooling plant positioning and network planning

Although buildings are the single largest users of energy in cities, many individual building HVAC (heating, ventilation, and air conditioning) systems are energy inefficient. Sustainable district heating and cooling systems have been developed to address this inefficiency, however, the implementation of district heating and cooling systems is a complex, capital intensive multivariate problem. One critical engineering problem, the location of energy production plant and pipe network topology, has a major influence on the system performance as well as the life cycle cost, and therefore should be comprehensively studied and chosen. This paper proposes a novel algorithmic design and decision-making framework that uses multiple simultaneous criteria to generate and evaluate design alternatives of site selection and pipe network layout. The framework consists of three components: site location and topology generation, network sizing and evaluation, and multi-objective decision-making assistance. The proposed framework has been validated in a real-world district cooling greenfield project in China's metropolitan area. Results were compared against the engineers’ best practices. It has shown that the proposed framework could find equally good or better designs in engineering and financial performance with CAPEX reduction of up to 15%.

Multiobjective Approach Toward Optimized Patch Repairs of Blisk Blades

Patching is a high-technology repair to preserve damaged jet engine blisks instead of replacing them. The damaged portion of the blade is restored by welding a patch to the blade. Since the extent of defects varies, the optimal repair is initially unknown. This work contributes to the design of patch repairs by employing multiobjective optimization. A multiobjective function is formulated, maximizing high cycle fatigue strength and minimizing the length of the weld. An inequality constraint equation ensures the complete removal of the damaged blade area. The geometry of the patch and the position of the defect are described using parametric models. Optimization results are presented for an exemplary damage scenario. The set of Pareto optimal alternatives is computed using nondominated sorting genetic algorithm II and imposing constraints by using a linear penalty approach. The results demonstrate that designs are found by the optimization that would not intuitively be recognized as optimal by maintenance technicians. Individual designs from the Pareto frontier are selected, and the welding process is analyzed in more detail using thermomechanical simulations. The distribution of residual stresses in the repaired blade is computed, and the influence on fatigue strength is determined. The multiobjective optimization and the finite element simulations implemented in the presented approach thus enable a systematic evaluation of design alternatives and support informed engineering decisions in the repair process.

Safety evaluation of design alternatives to separate freeway-opposing traffic

Objectives Different design alternatives used to separate freeway-opposing traffic may produce varying safety levels. State-of-the-art design guidelines have provided guidance in respect to a number of median features such as width, slope, and barrier installation. Guidance provided has been based on benefit-cost procedures; however, because project costs may significantly vary across different countries/jurisdictions, findings from benefit-cost procedures may be meaningless on a broader geographical scope. The objective of this study is to quantify the safety level of a number of design alternatives commonly used to separate opposing freeway traffic based solely on annualized crash costs. Methods The safety performance of 14 design alternatives were assessed using the Roadside Safety Analysis Program (RSAPv3). Results A test-level 3, low-tension cable barrier installed in the middle of a wide, hazard-free median was found to be the safest design alternative. Road sections containing: i) cable barriers were found to be safer than those containing w-beam guardrails, ii) low-tension cable barriers installed in the middle of the median were found to be safer than those containing high-tension cable barriers installed on one side of the median, regardless of median width, iii) wide, hazard-free medians were found to be safer than those containing WB guardrails, and iv) concrete barrier installations were found to be only safer than those containing unshielded medians, except when the median was 20 meters wide and hazard-free. Conclusions This paper not only provides evidence that some of the design alternatives often installed in real-world scenarios are not the safest, but it also discusses how some of these alternatives may not be the most cost-effective either. These findings make this study relevant and timely, as designers and policy/decision makers should always seek to maximize safety while optimizing the allocation of limited public funds.

Evaluating Mine Design Alternatives for Social Risks Using Discrete Choice Analysis

As with other engineering design tasks, mine design involves setting design objectives and constraints (the feasible solution space) and finding the optimal design alternative. Mine engineers often struggle to incorporate the preferences of local community members into their evaluation of mine design alternatives because the mining literature lacks tools to quantify such risks during mine planning. This paper presents an approach to evaluate community acceptance (i.e., community preferences for the alternatives) using discrete choice models and decision-based design during mine planning. Using discrete choice models and a rigorous framework, engineers can estimate the cost of social risks as a function of the probability that individuals in the host community will prefer a particular design alternative. They can then estimate the overall utility of a particular design alternative to the project proponents. This paper illustrates the proposed approach with a strategic mine planning exercise for a gold mine. The framework can be a useful tool for designing mines for sustainability, if combined with effective community engagement and management’s commitment to creating shared value.

Two-additive fuzzy measure-based information integration approach to product design alternative evaluation

Conceptual design is a pivotal stage of new product development in manufacturing industries. Since multiple design alternatives are put forward at this stage, developing advanced evaluation methods is of great importance. Existing methods adopt additive models to integrate evaluation data. They face some inconsistency issues, e.g. inconsistency in the independent assumption and interdependent data, since evaluation criteria are interactional. Fuzzy measure that replaces the additivity with monotonicity has enabled advances in addressing such issues. This work proposes a two-additive fuzzy measure-based information integration approach to product design alternative evaluation for the first time. The evaluation data given by experts are in the form of intuitionistic linguistic numbers. They are more in accordance with the thinking habits of experts because the hesitation degree in linguistic assessment can be revealed. In order to reduce the subjective bias, the decision-making trial and evaluation laboratory method combining with grey relational analysis is applied to adjust evaluation data. Then monotonous two-additive fuzzy measure is identified by nonlinear programming using these data. It makes a good trade-off between computational complexity and presentation capability. Hence, evaluation data can be integrated by non-additive Choquet integral for ranking design alternatives. In comparison to additive model-based methods, the extra effect on the simultaneous satisfaction of criteria can be effectively revealed by the proposed approach. And the robustness of it is demonstrated by the sensitivity analysis. A case study on an elevator's design alternative evaluation is conducted to illustrate the feasibility and practicability of the proposed approach.

Model based security verification of Cyber-Physical System based on Petrinet: A case study of Nuclear power plant

A variety of modern Cyber-Physical Systems (CPSs) are distributed and asynchronous systems that are becoming the backbone for smart infrastructures and systems such as smart grids, power plants, medical appliances, social robots etc. The weaving of cyber components with the physical system improves resource utilization and system reliability. However, it makes the CPSs significantly vulnerable to several cyber threats by increasing the attack surfaces. In safety-critical cyber-physical systems, the primary focus is on safety assurance. Any mistake or ignorance in security analysis may greatly amplify the losses in the presence of cyber threats. Such security failure may result in severe damages that may range from affecting critical infrastructures up to even loss of human lives. Thus, an early-staged security modeling of these systems is a prominent issue and requires a systematic approach for modeling a secure design as well as performance evaluation of alternative designs for the same. An in-depth security analysis involves the identification of a standard set of evaluation metrics. The proposed work provides the design-time methodology to map and analyze system security qualitatively and quantitatively using Stochastic Petri nets and their fundamental properties. The effectiveness of the proposed methodology is evaluated using a Nuclear power plant (NPP) case study.

A Consensus-Reaching Approach to the Evaluation of Product Design Alternatives with Multiple Preference Structures.

With interdisciplinarity being an important characteristic of contemporary product design, the evaluation of design alternatives also involves multiple disciplines, and the evaluator group usually consists of evaluators from different fields and with obvious heterogeneous characteristics. To effectively satisfy the heterogeneous needs of evaluators and improve the credibility of evaluation results, the paper introduces a consensus-reaching approach that incorporates multiple preferences to the evaluation of product design alternatives. First, in order to obtain individual preference information, each evaluator is asked to evaluate all the design alternatives using a preference structure that he/she is familiar with. Second, we use a transfer function to uniform the evaluation information obtained from various preference structures into a complementary judgment matrix. Then, we use the Hybrid Weighted Averaging (HWA) operator weight determination model to aggregate the preference information and obtain the group preference information. Then, we measure the consensus degree between individual evaluators and the group using a consensus measurement method. After that, we use the feedback mechanism to instruct individual evaluators to modify their preferences until a consensus is achieved. We explain the application steps and the feasibility of this approach through the evaluation of the design alternatives of multichannel fluorescence immunochromatography analyzers (MFIAs).

Microdissected "cuboids" for microfluidic drug testing of intact tissues.

As preclinical animal tests often do not accurately predict drug effects later observed in humans, most drugs under development fail to reach the market. Thus there is a critical need for functional drug testing platforms that use human, intact tissues to complement animal studies. To enable future multiplexed delivery of many drugs to one small biopsy, we have developed a multi-well microfluidic platform that selectively treats cuboidal-shaped microdissected tissues or "cuboids" with well-preserved tissue microenvironments. We create large numbers of uniformly-sized cuboids by semi-automated sectioning of tissue with a commercially available tissue chopper. Here we demonstrate the microdissection method on normal mouse liver, which we characterize with quantitative 3D imaging, and on human glioma xenograft tumors, which we evaluate after time in culture for viability and preservation of the microenvironment. The benefits of size uniformity include lower heterogeneity in future biological assays as well as facilitation of their physical manipulation by automation. Our prototype platform consists of a microfluidic circuit whose hydrodynamic traps immobilize the live cuboids in arrays at the bottom of a multi-well plate. Fluid dynamics simulations enabled the rapid evaluation of design alternatives and operational parameters. We demonstrate the proof-of-concept application of model soluble compounds such as dyes (CellTracker, Hoechst) and the cancer drug cisplatin. Upscaling of the microfluidic platform and microdissection method to larger arrays and numbers of cuboids could lead to direct testing of human tissues at high throughput, and thus could have a significant impact on drug discovery and personalized medicine.