Hypothetical Design Research Articles

Modeling the Effect of Flow Structure Selection on Residence Time in an Artificial Canal System: Case Study

A novel modeling approach was used to investigate the residence times of Oyster Cove, an artificial canal system connected to adjacent water bodies by unidirectional and bidirectional flow structures. A field program was carried out to evaluate and quantify the exchange of water through the system of flow structures and to gain an understanding of the mixing dynamics within the artificial canal. Results from the field program were also used to validate a three-dimensional circulation model and a flushing model used to quantify the existing residence time of the canal system. Finally, the model was used to compare several hypothetical design alternatives, to identify the effect on the canal's residence time, by changing the positions of the flow structures and using different combinations of structures. The comparison showed the significant improvements in residence times that could be achieved.

Renewable Energy Use Advantages of Maglev-Based Personal Rapid Transit

Maglev personal rapid transit (MPRT) is a personal rapid transit (PRT) system that uses renewable energy in usage, distribution, and generation. A PRT system provides on-demand service in a manner similar to the automobile. Different types of PRT have different impacts on the electrical grid load. Recent advances in power electronics and maglev technology allow for the design of a novel MPRT system characterized not only by exceptionally low power requirements but also by a unique capacity to incorporate energy distribution and storage infrastructure into the greater transportation architecture. A hypothetical hybrid MPRT design incorporating energy storage and transmission capabilities is described. In addition, thorough carbon dioxide and cost analyses are undertaken to more fully understand the spectrum of benefits of an MPRT solution, in comparison to conventional vehicle and plug-in hybrid electric vehicle approaches. An MPRT system not only offers significant advantages over other technologies in efficiently using renewable energy but also represents the unique potential to address urgent energy challenges by incorporating power transmission, storage, and generation infrastructure.

A Design Support Framework through Dynamic Deployment of Hypothesis and Verification in the Design Process

This paper proposes a design support framework, named DRIFT (Design Rationale Integration Framework of Three layers), which dynamically captures and manages hypothesis and verification in the design process. A core of DRIFT is a three-layered design process model of action, model operation and argumentation. This model integrates various design support tools and captures design operations performed on them. Action level captures the sequence of design operations. Model operation level captures the transition of design states, which records a design snapshot over design tools. Argumentation level captures the process of setting problems and alternatives. The linkage of three levels enables to automatically and efficiently capture and manage iterative hypothesis and verification processes through design operations over design tools. In DRIFT, such a linkage is extracted through the templates of design operations, which are extracted from the patterns embeded in design tools such as Design-For-X (DFX) approaches, and design tools are integrated through ontology-based representation of design concepts. An argumentation model, gIBIS (graphical Issue-Based Information System), is used for representing dependencies among problems and alternatives. A mechanism of TMS (Truth Maintenance System) is used for managing multiple hypothetical design stages. This paper also demonstrates a prototype implementation of DRIFT and its application to a simple design problem. Further, it is concluded with discussion of some future issues.

Effects of variations in hydrogeological parameters on water-table mounding in sandy loam and loamy sand soils beneath stormwater infiltration basins

The two-dimensional variably-saturated numerical model HYDRUS-2D, previously calibrated to recharge events from an infiltration basin, was used to predict water-table mounding under hypothetical basin design scenarios, and the primary factors that affect water-table mounding were evaluated. Infiltration basins are often utilized in urban environments to recharge stormwater to the aquifer. As a result of localized recharge beneath these basins, mound formation may reduce the thickness of the unsaturated zone available to filter pollutants and may reduce the infiltration rate of the basin. Understanding the effects of various physical factors on water-table mound formation is important for infiltration basin siting. For sandy loam and loamy sand subsurface materials, mound heights increased as the thickness of both the unsaturated and saturated zones decreased. Mound heights increased as the initial soil moisture, basin size and ponding depth increased. A thin sedimentation layer on the basin floor delayed mound formation, but only slightly decreased the maximum mound height. This analysis could be used in future selection of infiltration basin locations; however, the analysis is limited to conditions that represent only a select range of basin design conditions and parameters typical of a glacial till environment in Wisconsin, USA.

An exact reformulation-linearisation technique algorithm for solving a parameter extraction problem arising in compact thermal models

Compact thermal models (CTMs) are used to evaluate thermal characteristics of critical electronic chip packages under several hypothetical design and usage scenarios. In order to ensure that CTMs accurately estimate thermal response, an appropriate set of model parameters must first be selected. The challenge arising in this paper is to glean a set of parameters that best describes the performance of CTM over a set of test conditions. We examine a non-convex optimisation formulation for this parameter estimation problem, and derive the first exact optimisation algorithm for the problem using a continuous version of the reformulation-linearisation technique. We provide experimental results on real data to demonstrate the applicability of our approach.

Characteristics of the Gas Centrifuge for Uranium Enrichment and Their Relevance for Nuclear Weapon Proliferation

This article presents an analytical model, originally developed in the 1980s, for the gas centrifuge and uses this methodology to determine the main design and operational characteristics of several hypothetical centrifuge designs. A series of simulations for a typical first-generation machine is used to assess the relevance of important breakout scenarios, including batch recycling and cascade interconnection, using either natural uranium or preenriched material as feedstock.

Knowledge Discovery for Flyback-Booster Aerodynamic Wing Using Data Mining

Data mining has been performed on the results of an aerodynamic design optimization of a two-stage-to-orbit reusable launch vehicle flyback-booster wing. Three data mining techniques were compared, including selforganizing map, functional analysis of variance, and the rough set theory. The optimization problem had four aerodynamic objective functions and 71 wing shape design variables. The hypothetical design database resulting from the optimization contained a total of 302 solutions which included 102 nondominated solutions. Consequently, the acquired knowledge of the design space consisted of general design characteristics, correlation between objective functions, and the effects of these design variables on the objective functions, for both nondominated as well as all solutions. The comparison also revealed the similarities anddifferences among the three datamining techniques used in this study. Even though all three techniques discovered detailed design knowledge and the results produced by the combination of all three methods compensated disadvantages of each method when applied individually, it was discovered that the self-organizing map produced the overall best results. Moreover, this study has also shown that the knowledge acquired from both nondominated solutions and from all solutions found was consistent despite the differences between the design spaces. Furthermore, it was shown that datamining is essential for visualizing results of an evolutionary multi-objective optimization problem and extracting useful design knowledge from these results.

Islam and the Healthcare Environment: Designing Patient Rooms

Islam and the Muslim population are often the source of much misunderstanding and media-influenced misconceptions. Muslim patients who enter the healthcare environment are often weak and likely to experience feelings of vulnerability. Because of the complex and interwoven nature of culture and religion in a person's identity, it is important to consider patient belief systems and values when designing a patient's immediate environment. Through an exploration of literature related to culture and diversity and the beliefs and value system of the Muslim population, the authors were able to identify flexible design initiatives that could accommodate an array of cultural and spiritual practices. Islam and the Muslim population were chosen as the points of reference for this study because of the strong influence of the religion on the culture, and because of the many nuances that differ from the dominant culture within the United States. From these points of reference, a hypothetical design was developed for a patient room that considers differing notions of privacy, alternatives for cultural and religious practices, and ways to include symbolic meaning derived from attributes such as color.

Designing Cognitive Stimulating Environments for Infants and Toddlers

The purpose of the study was to review existing literature on the development of cognitive functioning and subsequent interpretations of environmental stimuli to develop an evidence–based hypothetical design for a prototype nursery to enhance the perception and cognition of infants and toddlers. To this end, literature on the cognitive development of both humans and animals was analyzed as it relates to the evolution of neurobiological processes to identify specific developmental capacities of infants and toddlers in the perception and detection of environmental stimuli. From this evidence–based knowledge, the researchers developed hypothetical designs as a starting point for further study. The methodology used for the study centered on a review of existing literature about biological and neurological development of sensory perception and the detection of stimuli. More specifically, the researchers looked at the neurobiological processes that enable infants and toddlers to detect sensation, and at the ways in which environmental sensations may be enhanced in order to strengthen neural connections. As part of this analysis, the researchers considered evolutionary perspectives, particularly as they relate to elements found in nature, and analyzed literature pertaining to children who were denied access to sensory stimulation during their formative years. The result was the development of a hypothetical prototype interior environment that could replicate the variations of basic stimulation patterns found within nature. The subsequent data were then analyzed and cross–referenced with existing research to form suppositions on safety and feasibility. The end result was the development of a prototype nursery as a hypothetical solution to enhancing sensory stimulation of children in their formative years, one that can now be implemented and studied further to determine its efficacy and impact on the development of infants and toddlers.

Improving evolutionary exploration to area-time optimization of FPGA designs

This paper presents a new methodology based on evolutionary multi-objective optimization (EMO) to synthesize multiple complex modules on reprogrammable devices. It starts from a behavioral description written in a common high-level language (for instance C) to automatically produce the register-transfer level (RTL) design in a hardware description language (e.g. Verilog). Since all high-level synthesis problems (scheduling, resource allocation and binding) are notoriously NP-complete and interdependent, these problems should be considered simultaneously. This drives to a wide design space, that needs to be thoroughly explored to obtain solutions able to satisfy the design constraints (e.g. area and performance). Since evolutionary algorithms are good candidates to tackle such complex explorations, in this paper we provide a solution based on the non-dominated sorting genetic algorithm (NSGA-II) to explore the design space and obtain the best solutions in terms of performance given the area constraints of a target reprogrammable device, for instance a Field Programmable Gate Array (FPGA). To further reduce the time needed for the exploration, that theoretically requires the complete logic synthesis of each visited point, the evaluation of the solutions have been speed-up by using two techniques: a good cost estimation model and a technique to exploit fitness inheritance by substituting the expensive actual evaluations with estimations based on closeness in an hypothetical design space. We show on the JPEG case study that the proposed approach provides good results in terms of trade-off between total area occupied and execution time. The results shows also that the Pareto-optimal set obtained by applying the proposed fitness inheritance model well approximates the set obtained without the proposed technique and reduces the overall execution time up to the 25% in average.

Analyses of single marker and pairwise effects of candidate loci for rheumatoid arthritis using logistic regression and random forests

Using parametric and nonparametric techniques, our study investigated the presence of single locus and pairwise effects between 20 markers of the Genetic Analysis Workshop 15 (GAW15) North American Rheumatoid Arthritis Consortium (NARAC) candidate gene data set (Problem 2), analyzing 463 independent patients and 855 controls. Specifically, our work examined the correspondence between logistic regression (LR) analysis of single-locus and pairwise interaction effects, and random forest (RF) single and joint importance measures. For this comparison, we selected small but stable RFs (500 trees), which showed strong correlations (r~0.98) between their importance measures and those by RFs grown on 5000 trees. Both RF importance measures captured most of the LR single-locus and pairwise interaction effects, while joint importance measures also corresponded to full LR models containing main and interaction effects. We furthermore showed that RF measures were particularly sensitive to data imputation. The most consistent pairwise effect on rheumatoid arthritis was found between two markers within MAP3K7IP2/SUMO4 on 6q25.1, although LR and RFs assigned different significance levels.Within a hypothetical two-stage design, pairwise LR analysis of all markers with significant RF single importance would have reduced the number of possible combinations in our small data set by 61%, whereas joint importance measures would have been less efficient for marker pair reduction. This suggests that RF single importance measures, which are able to detect a wide range of interaction effects and are computationally very efficient, might be exploited as pre-screening tool for larger association studies. Follow-up analysis, such as by LR, is required since RFs do not indicate high-risk genotype combinations.

Seismic base isolation using low-cost Scrap Tire Pads (STP)

This paper focuses on the experimental studies conducted on the development of no-cost seismic base isolation pads using scrap automobile tire pads (STP). The mechanical and dynamic properties of STP specimens made from different tire brands, with different number of layers, and orientations are evaluated experimentally. The tests are conducted using (a) axial compression tests, (b) lumped mass small displacement free vibration, and (c) large displacement (inclined plate and reverse-cyclic) static shear tests. The results of these STP tests are compared among themselves and against a commercially available laminated rubber bearing specimen. A general relationship has been proposed which formulates the stiffness differences between the two principal directions of rectangular pads. The paper includes three hypothetical design applications for the use of STPs. STPs are prepared by placing 18 cm × 20 cm cut tread sections layers of car tires on top each other. Larger size STPs can also be formed by placing longer strips of tread sections (integer multiples of tread width) side by side in alternating direction layers or using a woven structure. Test results have shown that the friction between tire layers is sufficient to keep layers intact. Although STP application cannot eliminate foundation-basement structural requirements, it presents advantages such as low-technology no-cost pad, weight reduction, ease of handling, simple shear stiffness adjustment by changing the number of layers, and environmental benefits by recycling scrap tires.

Decision analysis on fire safety design based on evaluating building fire risk to life

This study presents a framework of decision analysis on fire safety design alternatives based on evaluating building fire risk to life. A probabilistic risk assessment method for occupant life is presented with consideration of some uncertainties of evacuation process and fire development at first. For occupant evacuation time assessment, occupant pre-movement time is characterized by normal distribution. For onset time to untenable conditions assessment, its uncertainty is considered as probability distribution according to the range of design fires. Based on event tree technique, probable fire scenarios are analyzed with consideration of the effect of fire protection systems, employees extinguishing, etc. It is difficult to make a precise assessment on probability and consequence of every fire scenario, but their lower bound and upper bound can be achieved based on statistical data. Therefore, Supersoft Decision Theory [Malmnäs, P.E., 1995. Methods of Evaluation in Supersoft Decision Theory. Department of Philosophy, Stockholm University, 365 Stockholm; Johansson, H., Malmnäs, P.E., 2000. Application of supersoft decision theory in fire risk assessment. Journal of Fire Protection Engineering 14, 55–84] that allows decision maker to utilize vague statement is utilized to integrate with risk assessment to make decision on different fire safety design alternatives. To express how to make decision on different fire safety design alternatives based on evaluating building fire risk to life, two hypothetical fire safety design alternatives for a commercial building are presented.

Design of environmentally and socially conscious water metering tariffs for the UK

England is one of the few industrialised countries where water metering is not compulsory. Most households instead pay a fixed charge regardless of use. Yet water consumption is already at the limit of resources and beyond them in some regions. Despite the need to control demand, compulsory water metering has not been implemented largely because of concerns about the regressive impact on poorer households. This research analysed new data from Anglian Water on household water consumption and income to examine the distributional impacts of ten different hypothetical tariff designs. It was found that it was possible to design revenue-neutral metered tariffs that would cause only a small percentage of low-income households to lose and most to gain. With sensitive design, the social concerns about compulsory water metering can be dealt with.

Development of the enhanced self‐adaptive hybrid genetic algorithm (e‐SAHGA)

Genetic algorithms allow solution of more complex, nonlinear groundwater remediation design problems than traditional gradient‐based approaches, but they are more computationally intensive. One way to improve performance is through inclusion of local search, creating a hybrid genetic algorithm (HGA). The inclusion of local search helps to speed up the solution process and to make the solution technique more robust. This technical note focuses on the development and application of a new HGA, the enhanced self−adaptive hybrid genetic algorithm (e‐SAHGA), which is an enhancement of a previously developed HGA called SAHGA. The application of the e‐SAHGA algorithm to a hypothetical groundwater remediation design problem showed 90% reliability in identifying the optimal solution faster than the SGA, with average savings of 64% across 100 random initial populations. These results are considerably improved over SAHGA, which attained only 80% reliability and 14% average savings on the same initial populations.

Prediction of fragmentation and yield curves with reference to armourstone production

Armourstone production involves aspects of blast design and yield prediction. How they differ from methods drawn from experience in mining and aggregates blasting operations is examined. A number of possible blast fragmentation models and associated prediction methods are described, several being outlined in full. Their applicability to armourstone production and yield curve prediction is discussed by comparing model results based on a hypothetical armourstone blast design in a rock mass with realistic properties for an armourstone quarry. It is suggested that appropriate models for armourstone yield prediction will require some form of an in-situ block size distribution assessment. Such approaches rule out the standard application of the Kuz–Ram model. The recently reported ‘Swebrec’ function and associated prediction model, developed by the Swedish Blasting Research Centre, provides a promising replacement for the Rosin–Rammler based models for representing armourstone blast yield curves.

WE-E-330D-07: Empirical Studies of Polycrystalline Silicon-Based Flat-Panel Imagers Incorporating Pixel-Amplifiers

Purpose: To investigate the potential of achieving significant improvements in the DQE performance of active‐matrix flat‐panel imagers at low fluoroscopic exposures and high spatial frequencies through incorporation of novel pixel architectures based on polycrystallinesilicon thin‐film transistors(TFTs). Methods and Materials: Detailed empirical studies have recently been performed on the signal and noise characteristics of a series of arrays incorporating poly‐Si TFTs. These indirect detection designs involved three pixel architectures employing either a single TFT switch, a single‐stage amplifier, or a dual‐stage amplifier — along with a continuous photodiode structure. Determinations of MTF, NPS, and DQE, as well as of individual pixel properties (sensitivity, linearity, trapping, noise) were performed under fluoroscopic and radiographic conditions. Circuit simulations were also performed to explore the potential performance of these and other hypothetical array designs. Results: The studies indicate that the high mobilities of poly‐Si lead to potential frame rates of at least an order of magnitude greater than those of conventional arrays with a‐Si:H TFTs. In addition, the single‐ and dual‐stage pixel‐amplifier arrays demonstrate signal gain (∼×10 and ∼×25, respectively) very close to design expectations. Furthermore, empirical data taken from these early prototypes demonstrate a small, but non‐negligible enhancement in signal‐to‐noise performance compared to that of similar arrays using conventional designs, as a result of pixel amplification and the use of repeated, non‐destructive readout. Analysis based on these empirical results and circuit simulations indicates that, with circuit design optimization and improved TFT quality, further significant enhancement of performance should be possible. Conclusion: These results indicate that substantial improvements in DQE performance are possible through incorporation of poly‐Si circuits in flat panel pixel designs. Factors limiting the performance of present designs will be described and future steps in the development of this technology will be discussed. This work is supported by NIH grant R01 EB000558.

Optimal groundwater remediation design using an Adaptive Neural Network Genetic Algorithm

Large‐scale water resources optimization often involves using time‐consuming simulation models to evaluate potential water resource designs or calibrate parameter values. Approximation models have been proposed for improving computational efficiency of the optimization. In most instances, multiple simulation runs have been done prior to the optimization, which are then used to fit an approximate model that is used during the optimization. This paper demonstrates that this approach can lead to suboptimal solutions and proposes a dynamic modeling approach, called Adaptive Neural Network Genetic Algorithm (ANGA), in which artificial neural networks are adaptively and automatically trained directly within a genetic algorithm (GA) to replace the time‐consuming water resource simulation models. A dynamic learning approach is proposed to periodically sample new solutions both to update the ANNs and to correct the GA's convergence. Different configurations of ANGA were tested on a hypothetical groundwater remediation design case, and then the best configuration was applied to a field‐scale case. In these applications, ANGA saved 85–90% percent of the simulation model calls with no loss in accuracy of the optimal solutions. These results show that the method has substantial promise for reducing computational effort associated with large‐scale water resources optimization.

Assessing Variations in SPAD‐502 Chlorophyll Meter Measurements and Their Relationships with Nutrient Content of Trembling Aspen Foliage

The relative chlorophyll content in leaves estimated by the SPAD‐502 chlorophyll meter can be an efficient way to evaluate plant nitrogen (N) status in many crops and some tree species. In this study, the SPAD meter was used to look for relationships between relative leaf chlorophyll content and leaf nutrient concentration in trembling aspen. The variations in leaf chlorophyll measurements were also evaluated by using three sampling times and three measurement techniques. Hypothetical experimental designs were created to achieve better design efficiency. The best representation of overall leaf chlorophyll was found when six SPAD readings were taken at different locations on each leaf. There was a positive correlation between overall leaf N and estimated chlorophyll content, especially in the top part of the trees. Overall, this study suggested that the SPAD meter can give an estimation of trembling aspen nutritional status, especially if the differential partitioning of N within trees is considered.

Implementing lead‐free solders – the performance aspects

Purpose – To draw attention to the need to consider design and performance, as well as production, in the implementation of lead‐free solders.Design/methodology/approach – The potential failure modes of solder joints and their underlying causes are reviewed. A hypothetical design exercise is employed to demonstrate key requirements for reliable design.Findings – The substantial variation in influential mechanical properties over the ranges of stress, temperature and strain rate is likely to be encountered in service. In addition to these three parameters, there is the need to consider time‐temperature profiles in the service cycle and the prior thermal history of the joint materials.Originality/value – The demonstration that reliable design and life prediction can only be achieved by employing appropriate properties in appropriate constitutive expressions.