Conceptual Design As Novel Combination of Existing Device Features

1987 ◽  
Author(s):  
K. Ulrich ◽  
W. Seering
Keyword(s):  
Computational Complexity ◽  
Conceptual Design ◽  
Design Space ◽  
Effective Means ◽  
Trade Off ◽  
Computer Tools ◽  
Initial Stage ◽  
Design Languages ◽  
Structural Descriptions ◽  
Future Work

Abstract Conceptual design is the initial stage of the transformation between functional and structural descriptions of devices. Our primary aim is to develop ideas that will allow computer tools for conceptual design to be built. In this paper, we point out a fundamental trade-off between the expressiveness of design languages and the computational complexity of the resulting design problem. Research in computational conceptual design can therefore be viewed as the problem of defining a design language and then devising ways of controlling the size of the resulting design space. We propose that an effective means of controlling complexity is to use knowledge of existing designs to guide the synthesis of novel designs. We illustrate this concept with a program that designs novel mechanical fasteners from knowledge of existing fasteners. We analyze this experiment and highlight several areas for future work.

scholarly journals Configuration Study of Electric Helicopters for Urban Air Mobility

Aerospace ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 54
Author(s):  
Julia A. Cole ◽  
Lauren Rajauski ◽  
Andrew Loughran ◽  
Alexander Karpowicz ◽  
Stefanie Salinger
Keyword(s):  
Conceptual Design ◽  
Urban Areas ◽  
Design Space ◽  
Design Method ◽  
Urban Air ◽  
Main Rotor ◽  
Potential Benefits ◽  
Compound Helicopter ◽  
Configuration Changes

There is currently interest in the design of small electric vertical take-off and landing aircraft to alleviate ground traffic and congestion in major urban areas. To support progress in this area, a conceptual design method for single-main-rotor and lift-augmented compound electric helicopters has been developed. The design method was used to investigate the feasible design space for electric helicopters based on varying mission profiles and technology assumptions. Within the feasible design space, it was found that a crossover boundary exists as a function of cruise distance and hover time where the most efficient configuration changes from a single-main-rotor helicopter to a lift-augmented compound helicopter. In general, for longer cruise distances and shorter hover times, the lift-augmented compound helicopter is the more efficient configuration. An additional study was conducted to investigate the potential benefits of decoupling the main rotor from the tail rotor. This study showed that decoupling the main rotor and tail rotor has the potential to reduce the total mission energy required in all cases, allowing for increases in mission distances and hover times on the order of 5% for a given battery size.

scholarly journals Measure of Similarity between GMMs by Embedding of the Parameter Space That Preserves KL Divergence

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 957
Author(s):  
Branislav Popović ◽  
Lenka Cepova ◽  
Robert Cep ◽  
Marko Janev ◽  
Lidija Krstanović
Keyword(s):  
Computational Complexity ◽  
Parameter Space ◽  
Recognition Accuracy ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Dimensional Manifold ◽  
Dimensional Parameter ◽  
Trade Off ◽  
Measure Of Similarity ◽  
Lower Dimensional

In this work, we deliver a novel measure of similarity between Gaussian mixture models (GMMs) by neighborhood preserving embedding (NPE) of the parameter space, that projects components of GMMs, which by our assumption lie close to lower dimensional manifold. By doing so, we obtain a transformation from the original high-dimensional parameter space, into a much lower-dimensional resulting parameter space. Therefore, resolving the distance between two GMMs is reduced to (taking the account of the corresponding weights) calculating the distance between sets of lower-dimensional Euclidean vectors. Much better trade-off between the recognition accuracy and the computational complexity is achieved in comparison to measures utilizing distances between Gaussian components evaluated in the original parameter space. The proposed measure is much more efficient in machine learning tasks that operate on large data sets, as in such tasks, the required number of overall Gaussian components is always large. Artificial, as well as real-world experiments are conducted, showing much better trade-off between recognition accuracy and computational complexity of the proposed measure, in comparison to all baseline measures of similarity between GMMs tested in this paper.

MINIMIZING THE COMPLETE INFLUENCE TIME IN A SOCIAL NETWORK WITH STOCHASTIC COSTS FOR INFLUENCING NODES

2013 ◽  
Vol 21 (supp01) ◽  
pp. 63-74 ◽  
Author(s):  
YAODONG NI ◽  
QIAONI SHI
Keyword(s):  
Social Network ◽  
Computational Complexity ◽  
Stochastic Programming ◽  
Greedy Algorithm ◽  
Random Graphs ◽  
Minimum Time ◽  
Programming Models ◽  
Decision Criteria ◽  
Trade Off ◽  
The Cost

In this paper, we study the problem of targeting a set of individuals to trigger a cascade of influence in a social network such that the influence diffuses to all individuals with the minimum time, given that the cost of initially influencing each individual is with randomness and that the budget available is limited. We adopt the incremental chance model to characterize the diffusion of influence, and propose three stochastic programming models that correspond to three different decision criteria respectively. A modified greedy algorithm is presented to solve the proposed models, which can flexibly trade off between solution performance and computational complexity. Experiments are performed on random graphs, by which we show that the algorithm we present is effective.

Dependence of Early Engineering Concepts on Information Characteristics

1996 ◽  
Author(s):  
Willem G. Knoop ◽  
Ernest J. J. van Breemen ◽  
Joris S. M. Vergeest ◽  
Tjamme Wiegers
Keyword(s):  
Conceptual Design ◽  
Experimental Approach ◽  
Information Analysis ◽  
Experiment Data ◽  
Computer Tools ◽  
Conceptual Design Phase ◽  
Information Characteristics ◽  
Early Engineering ◽  
Activity Information

Abstract The expectations of computer tools to support the conceptual design phase are not yet met. An experimental approach to discover the use of information in conceptual design will give a realistic insight of the information requirements. This can be used to specify future computer support systems. A method to observe the use of information in a conceptual design process has recently been developed. The method has been tested and fine-tuned through the observation of 10 design sessions. Valuable empirical data resides from this experiment. Data has been analyzed in several perspectives. This paper presents the results of the activity/information analysis of the experiment in relation with the quality of the design concept. For the latter a rating system has been defined to quantify this. We have found a significant positive correlation of the amount of information that is communicated and the quality of the design. Furthermore a discussion is given on the relation between information and the activities of the designer. Analysis activities are more communication intensive compared to synthesis and evaluation tasks.

Chapter 34. Stochastic Boolean Satisfiability

2021 ◽  
Author(s):  
Stephen M. Majercik
Keyword(s):  
Artificial Intelligence ◽  
Computational Complexity ◽  
Probabilistic Reasoning ◽  
Broad Class ◽  
Theoretical Perspective ◽  
Boolean Satisfiability ◽  
Probabilistic Planning ◽  
Empirical Results ◽  
Future Work ◽  
Planning Problems

Stochastic satisfiability (SSAT) is an extension of satisfiability (SAT) that merges two important areas of artificial intelligence: logic and probabilistic reasoning. Initially suggested by Papadimitriou, who called it a “game against nature”, SSAT is interesting both from a theoretical perspective–it is complete for PSPACE, an important complexity class–and from a practical perspective–a broad class of probabilistic planning problems can be encoded and solved as SSAT instances. This chapter describes SSAT and its variants, their computational complexity, applications of SSAT, analytical results, algorithms and empirical results, related work, and directions for future work.

scholarly journals Teaching Genomic Pathology: Translating Team-Based Learning to a Virtual Environment Using Computer-Based Simulation

2018 ◽  
Vol 143 (4) ◽  
pp. 513-517 ◽  
Author(s):  
Richard L. Haspel ◽  
Asma M. Ali ◽  
Grace C. Huang ◽  
Matt H. Smith ◽  
James B. Atkinson ◽  
...  
Keyword(s):  
Virtual Environment ◽  
Skill Acquisition ◽  
Interactive Simulation ◽  
Residency Programs ◽  
Computer Tools ◽  
Team Based Learning ◽  
Post Test ◽  
Computer Based ◽  
Genomics Education ◽  
Future Work

Context.— Developing skills related to use of computer-based tools is critical for practicing genomic pathology. However, given the relative novelty of genomics education, residency programs may lack faculty members with adequate expertise and/or time to implement training. A virtual team-based learning (TBL) environment would make genomic pathology education available to more trainees. Objective.— To translate an extensively implemented in-person TBL genomic pathology workshop into a virtual environment and to evaluate both knowledge and skill acquisition. Design.— Using a novel interactive simulation approach, online modules were developed translating aspects of the TBL experience into the virtual environment with a goal of acquisition of necessary computer-related skills. The modules were evaluated at 10 postgraduate pathology training programs using a pre-post test design with participants deidentified. A postmodule anonymous survey obtained participant feedback on module quality and efficacy. Results.— There were 147 trainees who received an email request to voluntarily participate in the study. Of these, 43 trainees completed the pretest and 15 (35%) subsequently completed the posttest. Mean overall scores were 45% on the pretest compared with 70% on the posttest (P < .001; effect size = 1.4). Posttest improvement of results was similar for questions testing acquisition of knowledge versus skills. Regarding the 19 participants who took the survey, 18 (95%) would recommend the modules to others and believed they met the stated objectives. Conclusions.— A simulation-based approach allows motivated pathology trainees to acquire computer-related skills for practicing genomic pathology. Future work can explore efficacy in a nonvoluntary setting and adaptation to different specialties, learners, and computer tools.

A Review of Methods for the Geometric Post-Processing of Topology Optimized Models

2020 ◽  
Vol 20 (6) ◽  
Author(s):  
Subodh C. Subedi ◽  
Chaman Singh Verma ◽  
Krishnan Suresh
Keyword(s):  
Design Space ◽  
Poor Quality ◽  
Industrial Applications ◽  
Post Processing ◽  
Design Validation ◽  
Element Mesh ◽  
Parametric Control ◽  
Software Packages ◽  
Future Work ◽  
Testing Design

Abstract Topology optimization (TO) has rapidly evolved from an academic exercise into an exciting discipline with numerous industrial applications. Various TO algorithms have been established, and several commercial TO software packages are now available. However, a major challenge in TO is the post-processing of the optimized models for downstream applications. Typically, optimal topologies generated by TO are faceted (triangulated) models, extracted from an underlying finite element mesh. These triangulated models are dense, poor quality, and lack feature/parametric control. This poses serious challenges to downstream applications such as prototyping/testing, design validation, and design exploration. One strategy to address this issue is to directly impose downstream requirements as constraints in the TO algorithm. However, this not only restricts the design space, it may even lead to TO failure. Separation of post-processing from TO is more robust and flexible. The objective of this paper is to provide a critical review of various post-processing methods and categorize them based both on targeted applications and underlying strategies. The paper concludes with unresolved challenges and future work.

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