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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 217 records · Page 12

The numerical prediction of tornadic windstorms

Rather than treating localized severe weather events as being purely statistical in nature, a mathematical framework was developed based on the concept of a deterministic cascade of energy-momentum which bridges the gap between the longest and shortest of atmospheric wave phenomena. This cascade relieves macroscale wavelengths ( 1000 km) of mass-momentum imbalances by exciting convective phenomena ( 10 km) through a sophisticated transfer process involving intermediate, mesoscale wavelengths.

Paine, D. A.↗

An adaptive tracking observer for failure-detection systems

The design problem of adaptive observers applied to linear, constant and variable parameters, multi-input, multi-output systems, is considered. It is shown that, in order to keep the observer's (or Kalman filter) false-alarm rate (FAR) under a certain specified value, it is necessary to have an acceptable proper matching between the observer (or KF) model and the system parameters. An adaptive observer algorithm is introduced in order to maintain desired system-observer model matching, despite initial mismatching and/or system parameter variations. Only a properly designed adaptive observer is able to detect abrupt changes in the system (actuator, sensor failures, etc.) with adequate reliability and FAR. Conditions for convergence for the adaptive process were obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors and accurate and fast parameter identification, in both deterministic and stochastic cases.

Sidar, M.↗

Design of analytical failure detection using secondary observers

The problem of designing analytical failure-detection systems (FDS) for sensors and actuators, using observers, is addressed. The use of observers in FDS is related to the examination of the n-dimensional observer error vector which carries the necessary information on possible failures. The problem is that in practical systems, in which only some of the components of the state vector are measured, one has access only to the m-dimensional observer-output error vector, with m or = to n. In order to cope with these cases, a secondary observer is synthesized to reconstruct the entire observer-error vector from the observer output error vector. This approach leads toward the design of highly sensitive and reliable FDS, with the possibility of obtaining a unique fingerprint for every possible failure. In order to keep the observer's (or Kalman filter) false-alarm rate under a certain specified value, it is necessary to have an acceptable matching between the observer (or Kalman filter) models and the system parameters. A previously developed adaptive observer algorithm is used to maintain the desired system-observer model matching, despite initial mismatching or system parameter variations. Conditions for convergence for the adaptive process are obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors, while accurate and fast parameter identification, in both deterministic and stochastic cases, is obtained.

Sisar, M.↗

Composite Load Spectra for Select Space Propulsion Structural Components

Generic load models are described with multiple levels of progressive sophistication to simulate the composite (combined) load spectra (CLS) that are induced in space propulsion system components, representative of Space Shuttle Main Engines (SSME), such as transfer ducts, turbine blades and liquid oxygen (LOX) posts. These generic (coupled) models combine the deterministic models for composite load dynamic, acoustic, high-pressure and high rotational speed, etc., load simulation using statistically varying coefficients. These coefficients are then determined using advanced probabilistic simulation methods with and without strategically selected experimental data. The entire simulation process is included in a CLS computer code. Applications of the computer code to various components in conjunction with the PSAM (Probabilistic Structural Analysis Method) to perform probabilistic load evaluation and life prediction evaluations are also described to illustrate the effectiveness of the coupled model approach.

Ho, Hing W.↗

L'Ralph's Advanced Thermal Model Correlation Using Veritrek

Thermal model correlation uses data from thermal balance tests to better estimate uncertain input parameter values. During the correlation process, input parameters are modified in an iterative manner which can become computationally expensive since this requires that the high-fidelity thermal model be run for each iteration. Depending on the number of thermal balance test points there can be many sets of correlation parameters that satisfy correlation criteria; and having enough data to ascertain the best set of correlation parameters to use, further increases the computational expense. Reduced-order models (ROMs) provide computationally efficient surrogates of high-fidelity models and are often built to reduce development cycle times and cost. By leveraging the speed of reduced-order models and the Correlation Analysis feature in the Veritrek software, the typical computational expense of a traditional thermal model correlation process can be significantly reduced and having access to hundreds of thousands of iteration results provides an advanced means of intelligently determining the best set of correlation parameters to use. The L’Ralph thermal team at NASA Goddard Space Flight Center explored the use of the Veritrek software for their thermal model correlation efforts. The ROM that was created allowed for the variation of 15 input parameters to match 70 temperature sensor readouts from 3 thermal balance plateus and required 125 runs of the high-fidelity Thermal Desktop® model to generate a ROM that could predict the detailed model’s results to within 0.2 K (RMS). The ROM was then used to find dozens of plausible correlation parameter values based on L’Ralph instrument test data within a few seconds. By providing several plausible correlation parameter combinations, Veritrek allowed the thermal team to explore different uncertain parameter value combinations and provided insight into how deterministic each input parameter was. This allowed for a more confident decision on the best set of correlation parameters to use, compared to traditional model correlation techniques. In this presentation, the L’Ralph thermal team will be presenting their experience with the Veritrek software and how the software was utilized to provide additional insights during the correlation process.

Daniel Bae↗

L'Ralph's Advanced Thermal Model Correlation Using Veritrek

Thermal model correlation uses data from thermal balance tests to better estimate uncertain input parameter values. During the correlation process, input parameters are modified in an iterative manner which can become computationally expensive since this requires that the high-fidelity thermal model be run for each iteration. Depending on the number of thermal balance test points there can be many sets of correlation parameters that satisfy correlation criteria; and having enough data to ascertain the best set of correlation parameters to use, further increases the computational expense. Reduced-order models (ROMs) provide computationally efficient surrogates of high-fidelity models and are often built to reduce development cycle times and cost. By leveraging the speed of reduced-order models and the Correlation Analysis feature in the Veritrek software, the typical computational expense of a traditional thermal model correlation process can be significantly reduced and having access to hundreds of thousands of iteration results provides an advanced means of intelligently determining the best set of correlation parameters to use. The L’Ralph thermal team at NASA Goddard Space Flight Center explored the use of the Veritrek software for their thermal model correlation efforts. The ROM that was created allowed for the variation of 15 input parameters to match 70 temperature sensor readouts from 3 thermal balance plateus and required 125 runs of the high-fidelity Thermal Desktop® model to generate a ROM that could predict the detailed model’s results to within 0.2 K (RMS). The ROM was then used to find dozens of plausible correlation parameter values based on L’Ralph instrument test data within a few seconds. By providing several plausible correlation parameter combinations, Veritrek allowed the thermal team to explore different uncertain parameter value combinations and provided insight into how deterministic each input parameter was. This allowed for a more confident decision on the best set of correlation parameters to use, compared to traditional model correlation techniques. In this presentation, the L’Ralph thermal team will be presenting their experience with the Veritrek software and how the software was utilized to provide additional insights during the correlation process. "

Daniel Bae↗

SDIO Producibility and Manufacturing Intelligent Processing Programs

SDIO has to fashion a comprehensive strategy to insert the capability of an industrial base into ongoing design tradeoffs. This means that there is not only a need to determine if something can be made to the precision needed to meet system performance, but also what changes need to be made in that industry sector to develop a deterministic approach to fabrication precision components. Developing and introducing advanced production and quality control systems is part of this success. To address this situation, SDIO has developed the MODIL (Manufacturing Operations Development and Integration Labs) program. MODILs were developed into three areas: Survivable Optics, Electronics and Sensors, and Spacecraft Fabrication and Test.

Stottlemyer, Greg↗

Performance analysis and kernel size study of the Lynx real-time operating system

This paper analyzes the Lynx real-time operating system (LynxOS), which has been selected as the operating system for the Space Station Freedom Data Management System (DMS). The features of LynxOS are compared to other Unix-based operating system (OS). The tools for measuring the performance of LynxOS, which include a high-speed digital timer/counter board, a device driver program, and an application program, are analyzed. The timings for interrupt response, process creation and deletion, threads, semaphores, shared memory, and signals are measured. The memory size of the DMS Embedded Data Processor (EDP) is limited. Besides, virtual memory is not suitable for real-time applications because page swap timing may not be deterministic. Therefore, the DMS software, including LynxOS, has to fit in the main memory of an EDP. To reduce the LynxOS kernel size, the following steps are taken: analyzing the factors that influence the kernel size; identifying the modules of LynxOS that may not be needed in an EDP; adjusting the system parameters of LynxOS; reconfiguring the device drivers used in the LynxOS; and analyzing the symbol table. The reductions in kernel disk size, kernel memory size and total kernel size reduction from each step mentioned above are listed and analyzed.

Liu, Yuan-Kwei↗

Next Generation X-Ray Optics: High-Resolution, Light-Weight, and Low-Cost

X-ray telescopes are essential to the future of x-ray astronomy. This paper describes a comprehensive program to advance the technology for x-ray telescopes well beyond the state of the art represented by the three currently operating missions: Chandra, XMM-Newton , and Suzaku . This program will address the three key issues in making an x-ray telescope: (I) angular resolution, (2) effective area per unit mass, and (3) cost per unit effective area. The objectives of this technology program are (1) in the near term, to enable Explorer-class x-ray missions and an IXO type mission, and (2) in the long term, to enable a flagship x-ray mission with sub-arcsecond angular resolution and multi-square-meter effective area, at an affordable cost. We pursue two approaches concurrently, emphasizing the first approach in the near term (2-5 years) and the second in the long term (4-10 years). The first approach is precision slumping of borosilicate glass sheets. By design and choice at the outset, this technique makes lightweight and low-cost mirrors. The development program will continue to improve angular resolution, to enable the production of 5-arcsecond x-ray telescopes, to support Explorer-class missions and one or more missions to supersede the original IXO mission. The second approach is precision polishing and light-weighting of single-crystal silicon mirrors. This approach benefits from two recent commercial developments: (1) the inexpensive and abundant availability of large blocks of mono crystalline silicon, and (2) revolutionary advances in deterministic, precision polishing of mirrors. By design and choice at the outset, this technique is capable of producing lightweight mirrors with sub-arcsecond angular resolution. The development program will increase the efficiency and reduce the cost of the polishing and the lightweighting processes, to enable the production of lightweight sub-arcsecond x-ray telescopes. Concurrent with the fabrication of lightweight mirror segments is the continued development and perfection of alignment and integration techniques, for incorporating individual mirror segments into a precision mirror assembly. Recently, we have been developing a technique called edge-bonding, which has achieved an accuracy to enable 10- arcsecond x-ray telescopes. Currently, we are investigating and improving the long-term alignment stability of so-bonded mirrors. Next, we shall refine this process to enable 5-arsecond x-ray telescopes. This technology development program includes all elements to demonstrate progress toward TRL-6: metrology; x-ray performance tests; coupled structural, thermal, and optical performance analysis, and environmental testing.

Zhang, William W.↗

Third-Party Supplier Risk Re-Classification Using Multi-Model Semantic Voting and External Web Augmentation

Risk decisions in many third-party risk management (TPRM) workflows rely on static inherent risk questionnaires (IRQ). These static forms provide a snapshot of the vendor from the business users’ perspective, as these requests are processed without cross-referencing for evidence. Consequently, responses can be misinformed or embellished with inaccuracies, thereby masking the vendor’s true risk to the enterprise. This paper presents a multi-stage verification framework to augment IRQs with web evidence and a deterministic ensemble of large language model assessors to reclassify risk. In a case study of 100 submissions previously misclassified as low risk, the proposed framework correctly identified 76% of the cases as high risk, while the existing workflow identified none. McNemar’s continuity corrected statistics of 74 were obtained with a two sided p-value of 2.65 × 10-23, indicating a significantly more effective workflow compared to the legacy model.

99 - GENERAL AND MISCELLANEOUS↗

Modeling of the Reynolds stresses

In their most general form, the Reynolds averaged conservation equations result from ensemble or time averages of the instantaneous Navier-Stokes equations or their compressible counterparts. For these averaging processes to be consistent, the averaging time period must exceed the periods identified with the largest time scales of the turbulence, and yet be shorter than the characteristic times of the flow field. With these equations long period variations in the flow fields are deterministic, provided initial conditions are known. The average dependent variables are sufficiently smooth to be resolvable by finite difference techniques consistent with the size and speed of modern computers.

Rubesin, M. W.↗

Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation

We introduce a conditional pseudo-reversible normalizing flow (PR-NF) that directly learns conditional probability distributions from noisy physical models to efficiently quantify both forward and inverse uncertainty propagation. Traditional surrogate modeling approaches approximate only the deterministic component of physical models, requiring separate noise characterization and computationally expensive sampling methods for inverse problems. Here, in this work, we develop the conditional PR-NF model to directly learn and efficiently generate samples from the conditional probability density functions (PDFs). The training process utilizes dataset consisting of input-output pairs without requiring prior knowledge about the noise and the function. Once trained, our model efficiently generates samples from conditional PDFs for any input within the training domain. Moreover, the pseudo-reversibility feature allows for the use of fully connected neural network architectures, which simplifies the implementation and enables theoretical analysis. We provide a rigorous convergence analysis of the conditional PR-NF model, showing its ability to converge to the target conditional PDF using the Kullback−Leibler divergence. To demonstrate the effectiveness of our method, we apply it to several benchmark tests and a real-world geologic carbon storage problem.

97 MATHEMATICS AND COMPUTING↗

A multi-variance analysis in the time domain

Recently a new technique for characterizing the noise processes affecting oscillators was introduced. This technique minimizes the difference between the estimates of several different variances and their values as predicted by the standard power law model of noise. The method outlined makes two significant advancements: it uses exclusively time domain variances so that deterministic parameters such as linear frequency drift may be estimated, and it correctly fits the estimates using the chi-square distribution. These changes permit a more accurate fitting at long time intervals where there is the least information. This technique was applied to both simulated and real data with excellent results.

Walter, Todd↗

Automated Flight Routing Using Stochastic Dynamic Programming

Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.

Ng, Hok K.↗

Next Generation X-Ray Optics: High-Resolution, Light-Weight, and Low-Cost

X-ray telescopes are essential to the future of x-ray astronomy. In this talk I will describe a comprehensive program to advance the technology for x-ray telescopes well beyond the state of the art represented by the three currently operating missions: Chandra, XMM-Newton, and Suzaku. This program will address the three key issues in making an x-ray telescope: (1) angular resolution, (2) effective area per unit mass, and (3) cost per unit effective area. The objectives of this technology program are (1) in the near term, to enable Explorer-class x-ray missions and an IXO-type mission, and (2) in the long term, to enable a flagship x-ray mission with sub-arcsecond angular resolution and multi-square-meter effective area, at an affordable cost. We pursue two approaches concurrently, emphasizing the first approach in the near term (2-5 years) and the second in the long term (4-10 years). The first approach is precision slumping of borosilicate glass sheets. By design and choice at the outset, this technique makes lightweight and low-cost mirrors. The development program will continue to improve angular resolution, to enable the production of 5-arcsecond x-ray telescopes, to support Explorer-class missions and one or more missions to supersede the original IXO mission. The second approach is precision polishing and light-weighting of single-crystal silicon mirrors. This approach benefits from two recent commercial developments: (1) the inexpensive and abundant availability of large blocks of monocrystalline silicon, and (2) revolutionary advances in deterministic, precision polishing of mirrors. By design and choice at the outset, this technique is capable of producing lightweight mirrors with sub-arcsecond angular resolution. The development program will increase the efficiency and reduce the cost of the polishing and the light-weighting processes, to enable the production of lightweight sub-arcsecond x-ray telescopes. Concurrent with the fabrication of lightweight mirror segments is the continued development and perfection of alignment and integration techniques, for incorporating individual mirror segments into a precision mirror assembly. Recently, we have been developing a technique called edge-bonding, which has achieved an accuracy to enable 10-arcsecond x-ray telescopes. Currently, we are investigating and improving the long-term alignment stability of so-bonded mirrors. Next, we shall refine this process to enable 5-arsecond x-ray telescopes. This technology development program includes all elements to demonstrate progress toward TRL-6: metrology; x-ray performance tests; coupled structural, thermal, and optical performance analysis, and environmental testing.

Zhang, William W.↗

Use of probabilistic design methods for NASA applications

This paper presents a reliability evaluation process designed to improve the reliability of advanced launch systems. The work performed includes the development of a reliability prediction methodology to be used in the design phase of the Space Transportation Main Engine (STME). This includes prediction techniques which use historical data bases as well as deterministic and probabilistic engineering models for predicting design reliability. In summary, this paper describes a probabilistic design approach for the next-generation liquid rocket engine, the STME.

Safie, Fayssal M.↗

Learning In networks

Intelligent systems require software incorporating probabilistic reasoning, and often times learning. Networks provide a framework and methodology for creating this kind of software. This paper introduces network models based on chain graphs with deterministic nodes. Chain graphs are defined as a hierarchical combination of Bayesian and Markov networks. To model learning, plates on chain graphs are introduced to model independent samples. The paper concludes by discussing various operations that can be performed on chain graphs with plates as a simplification process or to generate learning algorithms.

Buntine, Wray L.↗

Architecture and Information Requirements to Assess and Predict Flight Safety Risks During Highly Autonomous Urban Flight Operations

As aviation adopts new and increasingly complex operational paradigms, vehicle types, and technologies to broaden airspace capability and efficiency, maintaining a safe system will require recognition and timely mitigation of new safety issues as they emerge and before significant consequences occur. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. In-time safety assurance comprises monitoring, assessment, and mitigation functions that proactively reduce risk in complex operational environments where the interplay of hazards may not be known (and therefore not accounted for) during design. These functions can also help to understand and predict emergent effects caused by the increased use of automation or autonomous functions that may exhibit unexpected non-deterministic behaviors. The envisioned monitoring and assessment functions can look for precursors, anomalies, and trends (PATs) by applying model-based and data-driven methods. Outputs would then drive downstream mitigation(s) if needed to reduce risk. These mitigations may be accomplished using traditional design revision processes or via operational (and sometimes automated) mechanisms. The latter refers to the ‘in-time’ aspect of the system concept. This report comprises architecture and information requirements and considerations toward enabling such a capability within the domain of low altitude highly autonomous urban flight operations. This domain may span, for example, public-use surveillance missions flown by small unmanned aircraft (e.g., infrastructure inspection, facility management, emergency response, law enforcement, and/or security) to transportation missions flown by larger aircraft that may carry passengers or deliver products. Caveat: Any stated requirements in this report should be considered initial requirements that are intended to drive research and development (R&D). These initial requirements are likely to evolve based on R&D findings, refinement of operational concepts, industry advances, and new industry or regulatory policies or standards related to safety assurance.

Young, Steven↗