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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7

All sources NASA NTRS DOE OSTI

NASA NTRS1989

Detecting and diagnosing SSME faults using an autoassociative neural network topology

An effort is underway at the University of Tennessee Space Institute to develop diagnostic expert system methodologies based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. Neural networks are being investigated as a means of storing and retrieving fault scenarios. Neural networks offer several powerful features in fault diagnosis, including (1) general pattern matching capabilities, (2) resistance to noisy input data, (3) the ability to be trained by example, and (4) the potential for implementation on parallel computer architectures. This paper presents (1) an autoassociative neural network topology, i.e. the network input and output is identical when properly trained, and hence learning is unsupervised; (2) the training regimen used; and (3) the response of the system to inputs representing both previously observed and unkown fault scenarios. The effects of noise on the integrity of the diagnosis are also evaluated.

Ali, M.↗

NASA NTRS1989

Space Shuttle Main Engine component assembly, assignment, and scheduling expert system

The SSME's Component Assembly and Life Management Expert System (CALMES) assists the engine assembly and scheduling process, ensuring that these activities utilize available resources with the greatest possible efficiency. On the basis of parts inventories and a proposed flight schedule, CALMES (1) determined how components may be optimally assembled from the parts inventory, (2) assigns components to flights, (3) schedules component testing, and (4) schedules component assembly. A graph-theoretical optimal matching algorithm, based on a modified simplex method, is applied to the major functions required by the SSME component assembly and scheduling processes.

Dietz, W. E.↗

NASA NTRS1994

Expert Witness: A system for developing expert medical testimony

Expert Witness in an expert system designed to assist attorneys and medical experts in determining the merit of medical malpractice claims in the area of obstetrics. It substitutes the time of the medical expert with the time of a paralegal assistant guided by the expert system during the initial investigation of the medical records and patient interviews. The product of the system is a narrative transcript containing important data, immediate conclusions from the data, and overall conclusions of the case that the attorney and medical expert use to make decisions about whether and how to proceed with the case. The transcript may also contain directives for gathering additional information needed for the case. The system is a modified heuristic classifier and is implemented using over 600 CLIPS rules together with a C-based user interface. The data abstraction and solution refinement are implemented directly using forward chaining production and matching. The use of CLIPS and C is essential to delivering a system that runs on a generic PC platform. The direct implementation in CLIPS together with locality of inference ensures that the system will scale gracefully. Two years of use has revealed no errors in the reasoning.

Lewandowski, Raymond↗

DOE OSTI2023

Plug & play directed evolution of proteins with gradient-based discrete MCMC

Abstract A long-standing goal of machine-learning-based protein engineering is to accelerate the discovery of novel mutations that improve the function of a known protein. We introduce a sampling framework for evolving proteins in silico that supports mixing and matching a variety of unsupervised models, such as protein language models, and supervised models that predict protein function from sequence. By composing these models, we aim to improve our ability to evaluate unseen mutations and constrain search to regions of sequence space likely to contain functional proteins. Our framework achieves this without any model fine-tuning or re-training by constructing a product of experts distribution directly in discrete protein space. Instead of resorting to brute force search or random sampling, which is typical of classic directed evolution, we introduce a fast Markov chain Monte Carlo sampler that uses gradients to propose promising mutations. We conduct in silico directed evolution experiments on wide fitness landscapes and across a range of different pre-trained unsupervised models, including a 650 M parameter protein language model. Our results demonstrate an ability to efficiently discover variants with high evolutionary likelihood as well as estimated activity multiple mutations away from a wild type protein, suggesting our sampler provides a practical and effective new paradigm for machine-learning-based protein engineering.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1996

Fuzzy Logic Decoupled Longitudinal Control for General Aviation Airplanes

It has been hypothesized that a human pilot uses the same set of generic skills to control a wide variety of aircraft. If this is true, then it should be possible to construct an electronic controller which embodies this generic skill set such that it can successfully control difference airplanes without being matched to a specific airplane. In an attempt to create such a system, a fuzzy logic controller was devised to control throttle position and another to control elevator position. These two controllers were used to control flight path angle and airspeed for both a piston powered single engine airplane simulation and a business jet simulation. Overspeed protection and stall protection were incorporated in the form of expert systems supervisors. It was found that by using the artificial intelligence techniques of fuzzy logic and expert systems, a generic longitudinal controller could be successfully used on two general aviation aircraft types that have very difference characteristics. These controllers worked for both airplanes over their entire flight envelopes including configuration changes. The controllers for both airplanes were identical except for airplane specific limits (maximum allowable airspeed, throttle lever travel, etc.). The controllers also handled configuration changes without mode switching or knowledge of the current configuration. This research validated the fact that the same fuzzy logic based controller can control two very different general aviation airplanes. It also developed the basic controller architecture and specific control parameters required for such a general controller.

Duerksen, Noel↗

NASA NTRS1997

Fuzzy Logic Decoupled Lateral Control for General Aviation Airplanes

It has been hypothesized that a human pilot uses the same set of generic skills to control a wide variety of aircraft. If this is true, then it should be possible to construct an electronic controller which embodies this generic skill set such that it can successfully control different airplanes without being matched to a specific airplane. In an attempt to create such a system, a fuzzy logic controller was devised to control aileron or roll spoiler position. This controller was used to control bank angle for both a piston powered single engine aileron equipped airplane simulation and a business jet simulation which used spoilers for primary roll control. Overspeed, stall and overbank protection were incorporated in the form of expert systems supervisors and weighted fuzzy rules. It was found that by using the artificial intelligence techniques of fuzzy logic and expert systems, a generic lateral controller could be successfully used on two general aviation aircraft types that have very different characteristics. These controllers worked for both airplanes over their entire flight envelopes. The controllers for both airplanes were identical except for airplane specific limits (maximum allowable airspeed, throttle ]ever travel, etc.). This research validated the fact that the same fuzzy logic based controller can control two very different general aviation airplanes. It also developed the basic controller architecture and specific control parameters required for such a general controller.

Duerksen, Noel↗

DOE OSTI2022

Using discrete Bayesian networks for diagnosing and isolating cross-level faults in HVAC systems

Fault detection and diagnosis (FDD) technologies are critical to ensure satisfactory building performance, such as reducing energy wastes and negative impacts on occupant comfort and productivity. Existing FDD technologies mainly focus on component-level FDD solutions, which could lead to mis-diagnosis of cross-level faults in heating, ventilating, and air-conditioning (HVAC) systems. Cross-level faults are those faults that occur in one component or subsystem, but cause operational abnormalities in other components or subsystems, and result in a building level performance degradation. How to effectively diagnose the root cause of a cross-level fault is the focus of this study. Here, this paper presents a novel discrete Bayesian Network (DisBN)-based method for diagnosing cross-level faults in an HVAC system commonly used in commercial buildings. A two-level DisBN structure model is developed in this study. The parameters used in the DisBN model are obtained either from expert knowledge or through machine-learning strategies from normal system operation data. Meanwhile, the probability parameters are discretized to incorporate the uncertainties associated with typical expert knowledge. Thus, the developed DisBN method addresses the challenges many other BN based FDD methods face, i.e., the lack of fault data for BN parameter training. The developed DisBN represents causal relationships between a fault and its cross-level system impacts (i.e., fault symptoms or fault indicators) by considering how fault impacts propagate across different levels in an HVAC system. A weather and schedule information-based Pattern Matching (WPM) method is employed to automatically create WPM baseline data sets for each incoming real time snapshot data from the building systems. Consequently, BN inference and real-time diagnostics are achieved by comparing incoming snapshot data and the WPM baseline data set. The proposed method is evaluated using experimental fault data collected in a campus building. Fault diagnosis results demonstrate that the WPM-DisBN method is effective at locating the root causes of cross-level faults in an HVAC system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Geography of Existing and Potential Alternative Fuel Markets in the United States

When deploying alternative fuels, it is paramount to match the right fuel with the right location, in accordance with local market conditions. We used six market indicators to evaluate the existing and potential regional market health for each of the five most commonly deployed alternative fuels: electricity (used by plug-in electric vehicles), biodiesel (blends of B20 and higher), E85 ethanol, compressed natural gas (CNG), and propane. Each market indicator was mapped, combined, and evaluated by industry experts. This process revealed the weight the market indicators should be given, with the proximity of fueling stations being the most important indicator, followed by alternative fuel vehicle density, gasoline prices, state incentives, nearby resources, and finally, environmental benefit. Though markets vary among states, no state received 'weak' potential for all five fuels, indicating that all states have an opportunity to use at least one alternative fuel. California, Illinois, Indiana, Pennsylvania, and Washington appear to have the best potential markets for alternative fuels in general, with each sporting strong markets for four of the fuels. Wyoming showed the least potential, with weak markets for all alternative fuels except for CNG, for which it has a patchy market. Of all the fuels, CNG is promising in the greatest number of states--largely because freight traffic provides potential demand for many far-reaching corridor markets and because the sources of CNG are so widespread geographically.

09 BIOMASS FUELS↗

NASA NTRS2000

Simulating the Composite Propellant Manufacturing Process

There is a strategic interest in understanding how the propellant manufacturing process contributes to military capabilities outside the United States. The paper will discuss how system dynamics (SD) has been applied to rapidly assess the capabilities and vulnerabilities of a specific composite propellant production complex. These facilities produce a commonly used solid propellant with military applications. The authors will explain how an SD model can be configured to match a specific production facility followed by a series of scenarios designed to analyze operational vulnerabilities. By using the simulation model to rapidly analyze operational risks, the analyst gains a better understanding of production complexities. There are several benefits of developing SD models to simulate chemical production. SD is an effective tool for characterizing complex problems, especially the production process where the cascading effect of outages quickly taxes common understanding. By programming expert knowledge into an SD application, these tools are transformed into a knowledge management resource that facilitates rapid learning without requiring years of experience in production operations. It also permits the analyst to rapidly respond to crisis situations and other time-sensitive missions. Most importantly, the quantitative understanding gained from applying the SD model lends itself to strategic analysis and planning.

Williamson, Suzanne↗

DOE OSTI2019

SunSpec Open Solar Data Exchange (oSDX) (Final Report)

Orange Button is a data interchange standard for solar finance and operations practitioners designed to drive down soft costs. To achieve its goals, SunSpec convened 330+ companies to validate Orange Button functional requirements. Approximately 4,000 industry-expert hours were invested to dissect 25 priority use cases and develop 4,500 Orange Button taxonomy entries and accompanying APIs. Orange Button 1.0 is now available on GitHub royalty-free to the general public. Early adopters include highly influential companies such as Aurora Solar, BayWa r.e., Clean Power Research, DNV-GL, LG, Mercatus, Oracle, Salesforce, sPower, SunPower, and Wells Fargo. Finally, the project was completed on time and on budget, including $2M match funding provided by industry.

14 SOLAR ENERGY↗

DOE OSTI2021

A vision of immuno-oncology: the Siena think tank of the Italian Network for Tumor Biotherapy (NIBIT) foundation

The yearly Think Tank Meeting of the Italian Network for Tumor Biotherapy (NIBIT) Foundation, brings together in Siena, Tuscany (Italy), experts in immuno-oncology to review the learnings from current immunotherapy treatments, and to propose new pre-clinical and clinical investigations in selected research areas. While immunotherapies in non-small cell lung cancer and melanoma led to practice changing therapies, the same therapies had only modest benefit for patients with other malignancies, such as mesothelioma and glioblastoma. One way to improve on current immunotherapies is to alter the sequence of each combination agent. Matching the immunotherapy to the host’s immune response may thus improve the activity of the current treatments. A second approach is to combine current immunotherapies with novel agents targeting complementary mechanisms. Identifying the appropriate novel agents may require different approaches than the traditional laboratory-based discovery work. For example, artificial intelligence-based research may help focusing the search for innovative and most promising combination partners. Novel immunotherapies are needed in cancer patients with resistance to or relapse after current immunotherapeutic drugs. Such new treatments may include targeted agents or monoclonal antibodies to overcome the immune-suppressive tumor microenvironment. The mode of combining the novel treatments, including vaccines, needs to be matched to the patient’s immune status for achieving the maximum benefit. In this scenario, specific attention should be also paid nowadays to the immune intersection between COVID-19 and cancer.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2010

New Mass Properties Engineers Aerospace Ballasting Challenge Facilitated by the SAWE Community

The discipline of Mass Properties Engineering tends to find the engineers; not typically vice versa. In this case, two engineers quickly found their new responsibilities deep in many aspects of mass properties engineering and required to meet technical challenges in a fast paced environment. As part of NASA's Constellation Program, a series of flight tests will be conducted to evaluate components of the new spacecraft launch vehicles. One of these tests is the Pad Abort 1 (PA-1) flight test which will test the Launch Abort System (LAS), a system designed to provide escape for astronauts in the event of an emergency. The Flight Test Articles (FTA) used in this flight test are required to match mass properties corresponding to the operational vehicle, which has a continually evolving design. Additionally, since the structure and subsystems for the Orion Crew Module (CM) FTA are simplified versions of the final product, thousands of pounds of ballast are necessary to achieve the desired mass properties. These new mass properties engineers are responsible for many mass properties aspects in support of the flight test, including meeting the ballasting challenge for the CM Boilerplate FTA. SAWE expert and experienced mass properties engineers, both those that are directly on the team and many that supported via a variety of Society venues, significantly contributed to facilitating the success of addressing this particular mass properties ballasting challenge, in addition to many other challenges along the way. This paper discusses the details regarding the technical aspects of this particular mass properties challenge, as well as identifies recommendations for new mass properties engineers that were learned from the SAWE community along the way.

Cutright, Amanda↗

DOE OSTI2023

Using an Absolute Cavity Pyrgeometer to Calibrate Pyrgeometers Outdoors with Respect to the International System of Units

Accurate measurement of the atmospheric longwave irradiance is important for renewable energy and atmospheric science applications. Pyrgeometers are deployed outdoors all over the world to measure the atmospheric longwave irradiance and presently are calibrated with traceability to the interim standards for atmospheric longwave radiation measurement, the standards are based on four pyrgeometers and their average irradiance is the World InfraRed Standard Group (WISG) which is developed and maintained by The Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC). Since 2013 the InfraRed Integrating Sphere (IRIS) developed by PMOD/WRC and the Absolute Cavity Pyrgeometer (ACP) developed by the National Renewable Energy Laboratory (NREL) have been compared outdoors six times at different locations and the difference between the measured atmospheric longwave irradiance by ACP and IRIS was less than 2 W/m2 with traceability to the International System of Units (SI). During the six comparisons the irradiance measured by the interim WISG was 5 W/m2 lower than the irradiance measured by the average irradiance measured by the ACP and IRIS [1]. Based on this discrepancy, the World Meteorological Organization's Commission for Instruments and Methods of Observation (CIMO) recommended that the interim WISG should be adjusted to be traceable to SI units [2]. In anticipation of CIMO's expert team agreement on establishing the world reference using the average irradiance measured by ACP and IRIS in this article we describe a procedure to calibrate pyrgeometers with traceability to SI. One Absolute Cavity Pyrgeometer (ACP95F3) was used to calibrate four pyrgeometers traceable to SI units. Three Eppley PIRs and one Kipp&Zonen CG4 were originally calibrated with traceability to the interim WISG. Using the described procedure below, the responsivity of each pyrgeometer was then adjusted to match the irradiance measured by ACP. Outdoor data was collected during one clear sky nights monitored by the output thermopile voltage of ACP95F3. The irradiance measured by the PIRs was calculated using NREL equation and the CG4 using NREL equation and PMOD/WRC equation. Using the NREL equation, the calculated uncertainty (U_95) of the PIRs varied from 2.43 W/m2 to 2.67 W/m2, and for the CG4 using the NREL equation U_95 equals 1.97 W/m2, and using the PMOD equation U_95 equals 2.88 W/m2 with respect to SI.

International System of Units↗

NASA NTRS1999

The NASA/MSFC Coherent Lidar Technology Advisory Team

The SPAce Readiness Coherent Lidar Experiment (SPARCLE) mission was proposed as a low cost technology demonstration mission, using a 2-micron, 100-mJ, 6-Hz, 25-cm, coherent lidar system based on demonstrated technology. SPARCLE was selected in late October 1997 to be NASA's New Millennium Program (NMP) second earth-observing (EO-2) mission. To maximize the success probability of SPARCLE, NASA/MSFC desired expert guidance in the areas of coherent laser radar (CLR) theory, CLR wind measurement, fielding of CLR systems, CLR alignment validation, and space lidar experience. This led to the formation of the NASA/MSFC Coherent Lidar Technology Advisory Team (CLTAT) in December 1997. A threefold purpose for the advisory team was identified as: 1) guidance to the SPARCLE mission, 2) advice regarding the roadmap of post-SPARCLE coherent Doppler wind lidar (CDWL) space missions and the desired matching technology development plan 3, and 3) general coherent lidar theory, simulation, hardware, and experiment information exchange. The current membership of the CLTAT is shown. Membership does not result in any NASA or other funding at this time. We envision the business of the CLTAT to be conducted mostly by email, teleconference, and occasional meetings. The three meetings of the CLTAT to date, in Jan. 1998, July 1998, and Jan. 1999, have all been collocated with previously scheduled meetings of the Working Group on Space-Based Lidar Winds. The meetings have been very productive. Topics discussed include the SPARCLE technology validation plan including pre-launch end-to-end testing, the space-based wind mission roadmap beyond SPARCLE and its implications on the resultant technology development, the current values and proposed future advancement in lidar system efficiency, and the difference between using single-mode fiber optical mixing vs. the traditional free space optical mixing.

Kavaya, Michael J.↗

NASA NTRS1999

Pre-Launch End-to-End Testing Plans for the SPAce Readiness Coherent Lidar Experiment (SPARCLE)

Kavaya, Michael J.↗

DOE OSTI2023

Using an Absolute Cavity Pyrgeometer to Calibrate Pyrgeometers Outdoors with Respect to the International System of Units

Accurate measurement of the atmospheric longwave irradiance is important for renewable energy and atmospheric science applications. Pyrgeometers are deployed outdoors all over the world to measure the atmospheric longwave irradiance and presently are calibrated with traceability to the interim standards for atmospheric longwave radiation measurement, the standards are based on four pyrgeometers and their average irradiance is the World InfraRed Standard Group (WISG) which is developed and maintained by The Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC). Since 2013 the InfraRed Integrating Sphere (IRIS) developed by PMOD/WRC and the Absolute Cavity Pyrgeometer (ACP) developed by the National Renewable Energy Laboratory (NREL) have been compared outdoors six times at different locations and the difference between the measured atmospheric longwave irradiance by ACP and IRIS was less than 2 w/m2 with traceability to the International System of Units (SI). During the six comparisons the irradiance measured by the interim WISG was 5 w/m2 lower than the irradiance measured by the average irradiance measured by the ACP and IRIS [1]. Based on this discrepancy, the World Meteorological Organization's Commission for Instruments and Methods of Observation (CIMO) recommended that the interim WISG should be adjusted to be traceable to SI units [2]. In anticipation of CIMO's expert team agreement on establishing the world reference using the average irradiance measured by ACP and IRIS in this article we describe a procedure to calibrate pyrgeometers with traceability to SI. One Absolute Cavity Pyrgeometer (ACP95F3) was used to calibrate four pyrgeometers traceable to SI units. Three Eppley PIRs and one Kipp&Zonen CG4 were originally calibrated with traceability to the interim WISG. Using the described procedure below, the responsivity of each pyrgeometer was then adjusted to match the irradiance measured by ACP. Outdoor data was collected during one clear sky night monitored by the output thermopile voltage of ACP95F3. The irradiance measured by the PIRs and CG4 was calculated using NREL equation. The calculated uncertainty (U95) of the PIRs varied from 2.43 w/m2 to 2.67 w/m2 , and for the CG4 equals 1.97 w/m2 with respect to SI.

absolute cavity pyrgeometer↗

NASA NTRS1989

Knowledge-based machine vision systems for space station automation

Computer vision techniques which have the potential for use on the space station and related applications are assessed. A knowledge-based vision system (expert vision system) and the development of a demonstration system for it are described. This system implements some of the capabilities that would be necessary in a machine vision system for the robot arm of the laboratory module in the space station. A Perceptics 9200e image processor, on a host VAXstation, was used to develop the demonstration system. In order to use realistic test images, photographs of actual space shuttle simulator panels were used. The system's capabilities of scene identification and scene matching are discussed.

Ranganath, Heggere S.↗

DOE OSTI2020

Evaporation Sub-model Development for Volume of Fluid (eVOF) Method Applicable to Spray-Wall Interaction Including Film Characteristics with Validation at High Pressure and Temperature Conditions (Final Report)

Internal combustion engines have seen a great evolution over the last several decades through application of high pressure direct injection, multiple injections, and other technologies to reduced fuel consumption, NOx, and PM. Although combustion systems with advanced injection strategies have been studied extensively, there exists a significant fundamental knowledge gap on the fuel-spray interactions with the piston surface and chamber walls. Advanced computational codes validated with experimental techniques have to be developed for accurate representation of the drop impingement, fuel film formation, and vaporization. Current engine CFD spray models utilize a Lagrangian framework for modeling which lacks critical considerations of the physics pertaining to these interactions and thus requiring extensive parameterization, tuning and validation. The team from Michigan Technological University, University of Massachusetts Dartmouth, and Argonne National Laboratory is composed of experts in sprays, combustion, engines and CFD with a wide spectrum of knowledge including specific expertise in the area under consideration. In the proposed work, a VOF modeling approach has been adopted for the spray-wall interaction, film formation and spreading, and vaporization. With the inclusion of a vaporization submodel, a more predictive and accurate simulation of the spray-film was performed without extensive need of parameterization and tuning. Extensive experimentation of the spray-wall interaction under the range of conditions matching the thermodynamic and surface temperatures that occur in diesel and gasoline engines were conducted to validate the SWI submodels and for development of the evaporation sub-model, which has been implemented in the Converge software.

42 ENGINEERING↗