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At least 1,621 records · Page 90

Variable-Complexity Multidisciplinary Optimization on Parallel Computers

This report covers work conducted under grant NAG1-1562 for the NASA High Performance Computing and Communications Program (HPCCP) from December 7, 1993, to December 31, 1997. The objective of the research was to develop new multidisciplinary design optimization (MDO) techniques which exploit parallel computing to reduce the computational burden of aircraft MDO. The design of the High-Speed Civil Transport (HSCT) air-craft was selected as a test case to demonstrate the utility of our MDO methods. The three major tasks of this research grant included: development of parallel multipoint approximation methods for the aerodynamic design of the HSCT, use of parallel multipoint approximation methods for structural optimization of the HSCT, mathematical and algorithmic development including support in the integration of parallel computation for items (1) and (2). These tasks have been accomplished with the development of a response surface methodology that incorporates multi-fidelity models. For the aerodynamic design we were able to optimize with up to 20 design variables using hundreds of expensive Euler analyses together with thousands of inexpensive linear theory simulations. We have thereby demonstrated the application of CFD to a large aerodynamic design problem. For the predicting structural weight we were able to combine hundreds of structural optimizations of refined finite element models with thousands of optimizations based on coarse models. Computations have been carried out on the Intel Paragon with up to 128 nodes. The parallel computation allowed us to perform combined aerodynamic-structural optimization using state of the art models of a complex aircraft configurations.

Grossman, Bernard↗

General purpose architecture for intelligent computer-aided training

An intelligent computer-aided training system having a general modular architecture is provided for use in a wide variety of training tasks and environments. It is comprised of a user interface which permits the trainee to access the same information available in the task environment and serves as a means for the trainee to assert actions to the system; a domain expert which is sufficiently intelligent to use the same information available to the trainee and carry out the task assigned to the trainee; a training session manager for examining the assertions made by the domain expert and by the trainee for evaluating such trainee assertions and providing guidance to the trainee which are appropriate to his acquired skill level; a trainee model which contains a history of the trainee interactions with the system together with summary evaluative data; an intelligent training scenario generator for designing increasingly complex training exercises based on the current skill level contained in the trainee model and on any weaknesses or deficiencies that the trainee has exhibited in previous interactions; and a blackboard that provides a common fact base for communication between the other components of the system. Preferably, the domain expert contains a list of 'mal-rules' which typifies errors that are usually made by novice trainees. Also preferably, the training session manager comprises an intelligent error detection means and an intelligent error handling means. The present invention utilizes a rule-based language having a control structure whereby a specific message passing protocol is utilized with respect to tasks which are procedural or step-by-step in structure. The rules can be activated by the trainee in any order to reach the solution by any valid or correct path.

Loftin, R. Bowen↗

Advective gas flow in bentonite: Development and comparison of enhanced multi-phase numerical approaches

Understanding the impact of repository gas, generated from degradation of waste and its interaction with the host rock, is essential when assessing the performance and safety function of long-term disposal systems for radioactive waste. Numerical models based on conventional multi-phase flow theory have historically been applied to predict the outcome and impact of gas flow on different repository components. However, they remain unable to describe the full complexity of the physical processes observed in water-saturated experiments (e.g., creation of dilatant pathways) and thus, the development of novel representations for their description is required when assessing fully saturated clay-based systems. This was the primary focus of Task A within the international cooperative project DECOVALEX-2019 (D-2019) and refinement of these approaches is the primary focus of this study (Task B in the current phase of DECOVALEX-2023). This paper summarises development of enhanced numerical representations of key processes and compares the performance of each model against high-quality laboratory test data. Experimental data reveals that gas percolation in water-saturated compacted bentonite is characterised by four key features: (i) a quiescence phase, followed by (ii) the gas breakthrough, which leads to a (iii) peak value, which is then followed by (iv) a negative decay. Three models based on the multiphase flow theory have been developed. These models can provide good initial values and reasonable responses for gas breakthrough (although some of them still predict a too-smooth response). Peak gas pressure values are in general reasonably well captured, although maximum radial stress differences are observed at 48 mm from the base of the sample. Here, numerical peak values of 12.8 MPa are predicted, whereas experimental values are about 11 MPa. These models are also capable of providing a reasonable representation of the negative pressure decay following peak pressure. However, other key specific features (such as the timing of gas breakthrough) still require a better representation. The model simulations and their comparison with experimental data show that these models need to be further improved with respect to model parameter calibration, the numerical representation of spatial heterogeneities in material properties and flow localisation, and the upscaling of the related physical processes and parameters. To further understand gas flow localisation, a new conceptual model has been developed, which shows that discrete channels can possibly be induced through the instability of gas-bentonite interface during gas injection, thus providing a new perspective for modeling gas percolation in low-permeability deformable media.

58 GEOSCIENCES↗

Cross-Categorical Transfer Learning based Composite Load Protection Modeling

Protection equipment is used to prevent damage to induction motor loads by isolating them from power systems in the event of severe faults. Modeling the response of induction motor loads and their protection is vital for power system planning and operation, especially in understanding system's dynamic performance and stability after a fault occurs. Induction motors are usually equipped with several types of protection with different operation mechanisms, making it challenging to develop adequate yet not overly complex protection models and determine their parameters for aggregate induction motor models. This paper proposes a novel cross-categorical transfer learning based framework to determine protection model parameters for aggregate induction motor loads in commercial buildings. Introducing a mathematical abstraction, the task of determining a suitable set of parameters for the protection model in composite load models is formulated as a combination of feature extraction using transferable layers, followed by affine operations through non-transferable layers applied on the previous extracted features. Numerical results are provided to illustrate the application of the framework.

transfer learning, Stacked Autoencoder, Composite ↗

PNNL-CompBio/perseq

Per sequence functional classification and Functional annotation in addition to linking those functions to taxonomic groups presents a challenge due to many established tools performing one task and not the other creating disparate downstream data. PerSeq aims to address these challenges by performing local alignments against a reference database annotated for both aspects, function and taxonomy, to annotate sequences individually. Downstream results are merged into count tables facilitating complex analyses based on observed function or functional potential in addition to being able to separate out function by taxonomic level to determine metabolic contributions by present organisms.

Brown, Joe↗

On the writing of programming systems for spacecraft computers.

Consideration of the systems designed to generate programs for the increasingly complex digital computers being used on board unmanned deep-space probes. Such programming systems must accommodate the special-purpose features incorporated in the hardware. The use of higher-level language facilities in the programming system can significantly simplify the task. Computers for Mariner and for the Outer Planets Grand Tour are briefly described, as well as their programming systems. Aspects of the higher level languages are considered.

Mathur, F. P.↗

Design and control strategies for CELSS - Integrating mechanistic paradigms and biological complexities

Systems analysis and control theory consideration are given to simulations of both individual components and total systems, in order to develop a reliable control strategy for a Controlled Ecological Life Support System (CELSS) which includes complex biological components. Because of the numerous nonlinearities and tight coupling within the biological component, classical control theory may be inadequate and the statistical analysis of factorial experiments more useful. The range in control characteristics of particular species may simplify the overall task by providing an appropriate balance of stability and controllability to match species function in the overall design. The ultimate goal of this research is the coordination of biological and mechanical subsystems in order to achieve a self-supporting environment.

Moore, B., III↗

Climatic Impact of a Change in North Atlantic Deep Water Formation

The response of the ocean to climate changes is one of the most uncertain questions regarding the impact of increasing CO2 on climate and society. North Atlantic deep water (NADW) formation apparently depends on a complex confluence of different water masses originating in different areas, all of which will presumably be affected by changes in wind, evaporation, etc., as the atmosphere warms. To analyze from first principles what the effect will be on NADW formation is a task which requires an ocean modeling capability not yet available. As a substitute, past climates can be investigated to see if there is any evidence for alterations in NADW formation. In addition, the possible impact of such changes on climate can be explored. An estimate of NADW sensitivity (at least in the past) and of the climate consequences can be studied. The North Atlantic surface water temperatures can be reconstructed to indicate a substantial cooling between 11,000 and 10,000 years B.P. Were NADW formation to have ceased, it would have resulted in cooler surface waters; whether the reconstructed temperatures were due to this or some other effect cannot be determined at this time. Nevertheless, it was decided that it would be useful to see what the effect these colder temperatures would have had on the climate.

Rind, D.↗

Space salvage - A report on Shuttle mission STS 51-A

The success of the Space Shuttle Orbiter and Manned Maneuvering Unit (MMU) in the rendezvous and capture of the Westar and Palapa satellites was largely attributable to the availability and fidelity of numerous simulators, which facilitated real time development and verification of satellite rescue procedures and hardware. This complex Space Shuttle mission, STS 51-A, was developed and executed in only 8 months; by contrast, the Solar Maximum repair mission was developed over a period of three years. Attention is presently given to Orbiter sensors, satellite night stationkeeping, satellite stabilization tasks, MMU tasks, and preparatory simulations.

Hauck, F. H.↗

Structural dynamics system model reduction

Loads analysis for structural dynamic systems is usually performed by finite element models. Because of the complexity of the structural system, the model contains large number of degree-of-freedom. The large model is necessary since details of the stress, loads and responses due to mission environments are computed. However, a simplified model is needed for other tasks such as pre-test analysis for modal testing, and control-structural interaction studies. A systematic method of model reduction for modal test analysis is presented. Perhaps it will be of some help in developing a simplified model for the control studies.

Chen, J. C.↗

ART/Ada design project, phase 1. Task 2 report: Detailed design

Various issues are studied in the context of the design of an Ada based expert system building tool. Using an existing successful design as a starting point, the impact is analyzed of the Ada language and Ada development methodologies on that design, the Ada system is redesigned, and its performance is analyzed using both complexity-theoretic and empirical techniques. The algorithms specified in the overall design are refined, resolving and documenting any open design issues, identifying each system module, documenting the internal architecture and control logic, and describing the primary data structures involved in the module.

Allen, Bradley P.↗

Space Station Furnace Facility. Volume 3: Program cost estimate

The approach used to estimate costs for the Space Station Furnace Facility (SSFF) is based on a computer program developed internally at Teledyne Brown Engineering (TBE). The program produces time-phased estimates of cost elements for each hardware component, based on experience with similar components. Engineering estimates of the degree of similarity or difference between the current project and the historical data is then used to adjust the computer-produced cost estimate and to fit it to the current project Work Breakdown Structure (WBS). The SSFF Concept as presented at the Requirements Definition Review (RDR) was used as the base configuration for the cost estimate. This program incorporates data on costs of previous projects and the allocation of those costs to the components of one of three, time-phased, generic WBS's. Input consists of a list of similar components for which cost data exist, number of interfaces with their type and complexity, identification of the extent to which previous designs are applicable, and programmatic data concerning schedules and miscellaneous data (travel, off-site assignments). Output is program cost in labor hours and material dollars, for each component, broken down by generic WBS task and program schedule phase.

Source record↗

Summary of a Crew-Centered Flight Deck Design Philosophy for High-Speed Civil Transport (HSCT) Aircraft

Past flight deck design practices used within the U.S. commercial transport aircraft industry have been highly successful in producing safe and efficient aircraft. However, recent advances in automation have changed the way pilots operate aircraft, and these changes make it necessary to reconsider overall flight deck design. Automated systems have become more complex and numerous, and often their inner functioning is partially or fully opaque to the flight crew. Recent accidents and incidents involving autoflight system mode awareness Dornheim, 1995) are an example. This increase in complexity raises pilot concerns about the trustworthiness of automation, and makes it difficult for the crew to be aware of all the intricacies of operation that may impact safe flight. While pilots remain ultimately responsible for mission success, performance of flight deck tasks has been more widely distributed across human and automated resources. Advances in sensor and data integration technologies now make far more information available than may be prudent to present to the flight crew.

Palmer, Michael T.↗

Evaluation of Technology Concepts for Traffic Data Management and Relevant Audio for Datalink in Commercial Airline Flight Decks

Datalink is currently operational for departure clearances and in oceanic environments and is currently being tested in high altitude domestic enroute airspace. Interaction with even simple datalink clearances may create more workload for flight crews than the voice system they replace if not carefully designed. Datalink may also introduce additional complexity for flight crews with hundreds of uplink messages now defined for use. Finally, flight crews may lose airspace awareness and operationally relevant information that they normally pickup from Air Traffic Control (ATC) voice communications with other aircraft (i.e., “party-line” transmissions). Once again, automation may be poised to increase workload on the flight deck for incremental benefit. Datalink implementation to support future air traffic management concepts needs to be carefully considered, understanding human communication norms and especially, the change from voice- to text-based communications modality and its effect on pilot workload and situation awareness. Increasingly autonomous systems, where autonomy is designed to support human-autonomy teaming, may be suited to solve these issues. NASA is conducting research and development of increasingly autonomous systems, utilizing machine-learning algorithms seamlessly integrated with humans whereby task performance of the combined system is significantly greater than the individual components. Increasingly autonomous systems offer the potential for significantly improved levels of performance and safety that are superior to either human or automation alone. Two increasingly autonomous systems concepts - a traffic data manager and a conversational co-pilot - were developed to intelligently address the datalink issues in a complex, future state environment with significant levels of traffic. The system was tested for suitability of datalink usage for terminal airspace. The traffic data manager allowed for automated declutter of the Automatic Dependent Surveillance-Broadcast (ADS-B) display. The system determined relevant traffic for display based on machine learning algorithms trained by experienced human pilot behaviors. The conversational co-pilot provided relevant audio air traffic control messages based on context and proximity to ownship. Both systems made use of the connected aircraft concepts to provide intelligent context to determine relevancy above and beyond proximity to ownship. A human-in-the-loop test was conducted in NASA Langley Research Center’s Integration Flight Deck B-737-800 simulator to evaluate the traffic data manager and the conversational co-pilot. Twelve airline crews flew various normal and non-normal procedures and their actions and performance were recorded in response to the procedural events. This paper details the flight crew performance and evaluation during the events.

Etherington, Timothy↗

Approach for energy efficient building design during early phase of design process

Energy consumption in the building sector is about 40% of total energy consumed globally and is trending upwards, along with its contribution to greenhouse gas (GHG) emissions. Given the adverse impacts of GHG emissions, it is crucial to integrate energy efficiency into building designs. The most significant opportunities for enhancing energy performance are present during the initial phases of building design, when there is less impact of other design constraints. Various tools exist for simulating different design options and providing feedback in terms of energy consumption and comfort parameters. These simulation outputs must then be analyzed to derive design solutions. This paper presents an innovative approach that utilizes user input parameters, processes them through cloud computing, and outputs easily understandable strategies for energy-efficient building design. The methodology employs Asynchronous Distributed Task Queues (DTQ) - a more scalable and reliable alternative to conventional speedup techniques-for conducting parametric energy simulations in the cloud. The goal of this approach is to assist design teams in identifying, visualizing, and prioritizing energy-saving design strategies from a range of possible solutions for each project. Furthermore, a tool ‘eDOT’ has been developed utilizing the discussed methodology. Unlike existing tools, eDOT leverages artificial intelligence to dynamically generate and provide design strategies during the early phases of design process. By simplifying the simulation process, eDOT enables design teams to make informed, data-driven decisions without needing to interpret complex simulation outputs. A case study simulated for two locations is provided in this paper to demonstrate the effectiveness of eDOT, further underscoring its practical impact on energy-efficient building design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Effects of cluster expansion on the locations of phase transition boundary as a first step to quantify uncertainty in first principles statistical mechanics framework

Predicting phase diagrams from first principle calculations eliminates the need of tedious experimental trials and errors. Fully automating first principle phase diagram calculations without any sort of human intervention has been a long daunting task and troubling scientific communities for decades. This grand problem remains not fully resolved, largely due to the vastly high-dimensional parameter space associated with density functional theory, cluster expansion, lattice Monte Carlo, and the substantial uncertainty propagating through a set of complex simulations. As a first step to tackle this grand problem, we reported a first demonstration of how sensitive phase boundary locations can be to various cluster expansion fittings and input DFT training data. To the best knowledge of the authors, this study reported the first ever attempt to quantify uncertainty in first principles statistical mechanics framework. In addition, a semi-automated phase transition detection algorithm has been devised in this paper to deal with the associated statistical errors and uncertainties from Monte Carlo method and its predecessor DFT calculations and cluster expansions. This algorithm has been applied in a classical cluster expansion Mg-Cd binary alloy system to detect phase transitions at various locations of phase diagram using different cluster expansions to demonstrate its predictive power and quantify uncertainties. The results suggested that using Chebyshev basis function shifted the transition locations toward the dilute solid solution phase and expanded the phase stability of concentrated ordered phases to wider composition range. The addition of perturbed defect configurations into training data set lowered the order-disorder transition temperature to be away from true transition temperature, suggesting the transition nature is indeed configurational disorder dominated rather than defect assisted. Finally, we found that the weighting has negligible effect on the transition locations, except for the case of using Chebyshev basis function to fit all non-weighted configurations that can be susceptible to Monte Carlo sampling hysteresis.

36 MATERIALS SCIENCE↗

Data Fusion via Neural Network Entropy Minimization for Target Detection and Multi-Sensor Event Classification

Broadly applicable solutions to multimodal and multisensory fusion problems across domains remain a challenge because effective solutions often require substantive domain knowledge and engineering. The chief questions that arise for data fusion are in when to share information from different data sources, and how to accomplish the integration of information. The solutions explored in this work remain agnostic to input representation and terminal decision fusion approaches by sharing information through the learning objective as a compound objective function. The objective function this work uses assumes a one-to-one learning paradigm within a one-to-many domain which allows the assumption that consistency can be enforced across the one-to-many dimension. The domains and tasks we explore in this work include multi-sensor fusion for seismic event location and multimodal hyperspectral target discrimination. We find that our domain- informed consistency objectives are challenging to implement in stable and successful learning because of intersections between inherent data complexity and practical parameter optimization. While multimodal hyperspectral target discrimination was not enhanced across a range of different experiments by the fusion strategies put forward in this work, seismic event location benefited substantially, but only for label-limited scenarios.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Techniques of subjective workload assessment - A comparison of two methodologies

With increasing complexity of systems, evaluation techniques based on close examination of an operator's performance become more and more difficult to perform, and it is much easier to base on evaluation of a workload on the opinion of the operator involved in performing the task. The present paper has the objective to compare two of the general subjective workload assessment techniques which have been developed. One of these techniques, the Subjective Workload Assessment Technique (SWAT), has been developed primarily at the USAF Aerospace Medical Research Laboratory for use in cockpit environments. The second technique, the NASA weighted-bipolar technique, is a development tool to examine the underlying relationships among many factors. One of the two goals of the study is concerned with the general validity of subjective workload assessments, while, according to the second goal, any particular strengths or weaknesses with respect to either of the two techniques are to be observed. It is concluded that both techniques appear to be worthwhile.

Vidulich, M. A.↗