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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 1,189 records · Page 66

A Performance Prediction Model for a Fault-Tolerant Computer During Recovery and Restoration

The modeling and design of a fault-tolerant multiprocessor system is addressed. In particular, the behavior of the system during recovery and restoration after a fault has occurred is investigated. Given that a multicomputer system is designed using the Algorithm to Architecture to Mapping Model (ATAMM), and that a fault (death of a computing resource) occurs during its normal steady-state operation, a model is presented as a viable research tool for predicting the performance bounds of the system during its recovery and restoration phases. Furthermore, the bounds of the performance behavior of the system during this transient mode can be assessed. These bounds include: time to recover from the fault (t(sub rec)), time to restore the system (t(sub rec)) and whether there is a permanent delay in the system's Time Between Input and Output (TBIO) after the system has reached a steady state. An implementation of an ATAMM based computer was developed with the Generic VHSIC Spaceborne Computer (GVSC) as the target system. A simulation of the GVSC was also written based on the code used in ATAMM Multicomputer Operating System (AMOS). The simulation is in turn used to validate the new model in the usefulness and accuracy in tracking the propagation of the delay through the system and predicting the behavior in the transient state of recovery and restoration. The model is validated as an accurate method to predict the transient behavior of an ATAMM based multicomputer during recovery and restoration.

Stoughton, John W.↗

A micromirror array with annular partitioning for high-speed random-access axial focusing

Dynamic axial focusing functionality has recently experienced widespread incorporation in microscopy, augmented/virtual reality (AR/VR), adaptive optics and material processing. However, the limitations of existing varifocal tools continue to beset the performance capabilities and operating overhead of the optical systems that mobilize such functionality. The varifocal tools that are the least burdensome to operate (e.g. liquid crystal, elastomeric or optofluidic lenses) suffer from low (≈100 Hz) refresh rates. Conversely, the fastest devices sacrifice either critical capabilities such as their dwelling capacity (e.g. acoustic gradient lenses or monolithic micromechanical mirrors) or low operating overhead (e.g. deformable mirrors). Here, we present a general-purpose random-access axial focusing device that bridges these previously conflicting features of high speed, dwelling capacity and lightweight drive by employing low-rigidity micromirrors that exploit the robustness of defocusing phase profiles. Geometrically, the device consists of an 8.2 mm diameter array of piston-motion and 48-μm-pitch micromirror pixels that provide 2π phase shifting for wavelengths shorter than 1100 nm with 10–90% settling in 64.8 μs (i.e., 15.44 kHz refresh rate). The pixels are electrically partitioned into 32 rings for a driving scheme that enables phase-wrapped operation with circular symmetry and requires <30 V per channel. Optical experiments demonstrated the array’s wide focusing range with a measured ability to target 29 distinct resolvable depth planes. Overall, the features of the proposed array offer the potential for compact, straightforward methods of tackling bottlenecked applications, including high-throughput single-cell targeting in neurobiology and the delivery of dense 3D visual information in AR/VR.

42 ENGINEERING↗

Detection of Periodic Forced Oscillations in Power Systems

An algorithm for the detection and frequency estimation of forced oscillations in power systems is proposed. The method operates by comparing the periodogram of synchrophasor measurements to a detection threshold. This threshold is established by deriving a general expression for the distribution of the periodogram and is related to the algorithm's probabilities of false alarm and detection. Unlike classic detection algorithms designed for use with white Gaussian noise, the proposed algorithm uses a detection threshold that varies with frequency to account for the colored nature of synchrophasor measurements. Further, a detection scheme based on multiple segments of data is proposed to improve the algorithm's performance as a monitoring tool in the online environment. A design approach that helps to ensure that the best-available probability of detection from any one detection segment is constantly increasing with the duration of the forced oscillation is also developed. Results from application of the detection algorithm to simulated and measured power system data suggest that the algorithm provides the expected detection performance and can be used to detect forced oscillations in practical monitoring of power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Measurements and Predictions for a Distributed Exhaust Nozzle

The acoustic and aerodynamic performance characteristics of a distributed exhaust nozzle (DEN) design concept were evaluated experimentally and analytically with the purpose of developing a design methodology for developing future DEN technology. Aerodynamic and acoustic measurements were made to evaluate the DEN performance and the CFD design tool. While the CFD approach did provide an excellent prediction of the flowfield and aerodynamic performance characteristics of the DEN and 2D reference nozzle, the measured acoustic suppression potential of this particular DEN was low. The measurements and predictions indicated that the mini-exhaust jets comprising the distributed exhaust coalesced back into a single stream jet very shortly after leaving the nozzles. Even so, the database provided here will be useful for future distributed exhaust designs with greater noise reduction and aerodynamic performance potential.

Kinzie, Kevin W.↗

Comparative Analysis of HEATNETS for Geothermal Network Performance

Thermal energy networks (TENs), also known as 5th generation district energy systems, or more specifically geothermal networks when exchanging heat with geothermal boreholes, are an important technology for decarbonization. In these networks an ambient loop connects buildings and thermal sources, such as a borehole field, to exchange energy and maintain a desired loop temperature. Water-source heat pumps are used at the buildings to connect to the ambient or thermal loop to meet to the building heating and cooling loads and maintain comfort. A semi-transient, reduced-order technical model and techno-economic model, called HEATNETS, has been developed at NREL that captures the flow of energy around a TEN. In this work, a comparison of the HEATNETS technical model and a well-known coding platform used for modeling geothermal networks, TRNSYS, has been completed for a proposed geothermal network as a verification and validation process. Hourly data provided from the TRNSYS simulation included building loads, pumping power, heat pump power, temperature entering and leaving the borehole field, and mass flow rates. The hourly borehole temperatures were used to create a linear regression model utilized in HEATNETS to estimate the borehole field heat exchange. The building loads and mass flow rates were direct inputs to HEATNETS while the pumping power, heat pump power, borehole temperatures, and coefficients of performance were all simulated and calculated by HEATNETS, allowing for direct comparison of the thermal energy transfer HEATNETS considers the full process from design inputs to economic outputs and can provide modeling options for high-level initial system design and operational optimization. This study focuses on a validation of HEATNETS using results from TRNSYS. HEATNETS is not intended to replace other modeling tools, but this work demonstrates, via a comparison with an industry standard code, that HEATNETS can be a unique, high-level and rapid modeling tool for estimating the performance of a full geothermal network system.

15 GEOTHERMAL ENERGY↗

Space Shuttle Main Engine performance analysis

For a number of years, NASA has relied primarily upon periodically updated versions of Rocketdyne's power balance model (PBM) to provide space shuttle main engine (SSME) steady-state performance prediction. A recent computational study indicated that PBM predictions do not satisfy fundamental energy conservation principles. More recently, SSME test results provided by the Technology Test Bed (TTB) program have indicated significant discrepancies between PBM flow and temperature predictions and TTB observations. Results of these investigations have diminished confidence in the predictions provided by PBM, and motivated the development of new computational tools for supporting SSME performance analysis. A multivariate least squares regression algorithm was developed and implemented during this effort in order to efficiently characterize TTB data. This procedure, called the 'gains model,' was used to approximate the variation of SSME performance parameters such as flow rate, pressure, temperature, speed, and assorted hardware characteristics in terms of six assumed independent influences. These six influences were engine power level, mixture ratio, fuel inlet pressure and temperature, and oxidizer inlet pressure and temperature. A BFGS optimization algorithm provided the base procedure for determining regression coefficients for both linear and full quadratic approximations of parameter variation. Statistical information relative to data deviation from regression derived relations was also computed. A new strategy for integrating test data with theoretical performance prediction was also investigated. The current integration procedure employed by PBM treats test data as pristine and adjusts hardware characteristics in a heuristic manner to achieve engine balance. Within PBM, this integration procedure is called 'data reduction.' By contrast, the new data integration procedure, termed 'reconciliation,' uses mathematical optimization techniques, and requires both measurement and balance uncertainty estimates. The reconciler attempts to select operational parameters that minimize the difference between theoretical prediction and observation. Selected values are further constrained to fall within measurement uncertainty limits and to satisfy fundamental physical relations (mass conservation, energy conservation, pressure drop relations, etc.) within uncertainty estimates for all SSME subsystems. The parameter selection problem described above is a traditional nonlinear programming problem. The reconciler employs a mixed penalty method to determine optimum values of SSME operating parameters associated with this problem formulation.

Santi, L. Michael↗

Development and Performance Evaluation of of Active Insulation Systems using Solid-State Thermal Switches

Traditional building envelopes have passive insulation systems that cannot respond to dynamic changes in the environment. An Active Insulation System (AIS) consists of Active Insulation Materials (AIMs), which dynamically vary the thermal conductivity of the insulation system. Several researchers have evaluated the impact of AIS on building thermal and energy performance by using simulation tools. Up to 70% savings in annual heating and cooling energy and significant reductions in peak demand have been predicted for some climates with wall systems employing AIS. Sensitivity studies have provided requirements for the AIS properties and control schemes that can lead to those savings. However, materials and assembly development have not yet achieved a cost-effective product that achieves the required performance. In this study, we present the process to develop an AIS that we will install in a test hut for their performance evaluation. Minimum performance criteria of the AIS system are developed based on Rmin/Rmax ratio, required time and efficiency to switch states and cost estimate. The next step carried out during this study is creating the concept to meet the requirements, predicting the performance by simulations, developing the experimental setup for bench-scale testing, and finally, constructing a full-scale wall assembly and monitoring the performance when exposed to natural weather conditions. The selected approach uses off-the-shelf products to create a materials system that can switch R-value between R~=1 ft2·°F·h/BTU (0.18 m2·K/W) and R~=7 ft2·°F·h/BTU (1.23 m2·K/W and have a switching time of less than one minute between R-high and R-low.

Iffa, Emishaw↗

The effects of long delay and transmission errors on the performance of TP-4 implementations

A set of tools that allows us to measure and examine the effects of transmission delay and errors on the performance of TP-4 implementations has been developed. The tools give insight into both the large- and small-scale behaviors of an implementation. These tools have been systematically applied to a commercial implementation of TP-4. Measurements show, among other things, that a 2-second one-way transmission delay and an effective bit-error rate of 1 error per 100,000 bits can result in a 95 percent reduction in TP-4 throughput. The detailed statistics give insight into why transmission delay and errors affect this implementations so significantly and support a number of 'lessons learned' that could be applied to TP-4 implementations that operate more robustly across networks with long transmission delays and transmission errors.

Durst, Robert C.↗

Distant Observer™ [SWR-12-09]

Distant Observer™ (DO) is an optical measurement tool, designed for parabolic trough solar collectors, that determines reflector slope error, absorber position error, and the combined errors based on images of the receiver-tube reflection taken from different angles. We have demonstrated that DO can provide a measurement accuracy of 0.25 mrad for the slope and receiver position errors. DO has two implementation versions: ground-based and drone-driven. As we pursue efforts to lower the capital and installation costs of parabolic trough solar collectors, it is essential to maintain high optical performance. The Distant Observer™ (DO) tool, developed by engineers at NREL, is a fast and highly accurate tool that provides complete characterization of the performance of the optical components which include the mirror panels and thermal receiver. This tool is very useful for testing both prototype and operational modules. The Distant Observer™ is an optical measurement tool for parabolic solar collectors that measures reflector slope error, absorber position error and the combined errors. Reflector slope errors occur for many reasons including imperfection in structural frame design, manufacturing and assembly. Absorber position error can be caused by poor structural design, poor installation, sag from the absorber weight, or change in the structure over time.

Ihas, Benjamin↗

Mechanistic materials modeling for nuclear fuel performance

Fuel performance codes are critical tools for the design, certification, and safety analysis of nuclear reactors. However, their ability to predict fuel behavior under abnormal conditions is severely limited by their considerable reliance on empirical materials models correlated to burn-up (a measure of the number of fission events that have occurred, but not a unique measure of the history of the material). In this paper, we propose a different paradigm for fuel performance codes to employ mechanistic materials models that are based on the current state of the evolving microstructure rather than burn-up. In this approach, a series of state variables are stored at material points and define the current state of the microstructure. The evolution of these state variables is defined by mechanistic models that are functions of fuel conditions and other state variables. The material properties of the fuel and cladding are determined from microstructure/property relationships that are functions of the state variables and the current fuel conditions. Multiscale modeling and simulation is being used in conjunction with experimental data to inform the development of these models. Finally, this mechanistic, microstructure-based approach has the potential to provide a more predictive fuel performance capability, but will require a team of researchers to complete the required development and to validate the approach.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Toward the Detection of Polyglot Files

Standardized file types play a key role in the development and use of computer software. However, it is possible to confound standardized file type processing by creating a file that is valid in multiple file types. The resulting polyglot (many languages) file can confuse file type identification, allowing elements of the file to evade analysis. This is especially problematic for malware detection systems that rely on file type identification for feature extraction. Although work has been done to identify file types using more comprehensive methods than file signatures, accurate identification of polyglot files remains an open problem. Since malware detection systems routinely perform file type-specific feature extraction, polyglot files need to be filtered out prior to ingestion by these systems. Otherwise, malicious content could pass through undetected. To address the problem of polyglot detection we assembled a data set using the mitra tool. We then evaluated the performance of the most commonly used file identification tools, including file, polydet, binwalk, and TrID. Our analysis demonstrates that existing file type detection tools fail to provide reliable polyglot detection. We then evaluated the ability of a range of machine and deep learning models to detect polyglot files. The most performant models were MalConv2 and Catboost, which demonstrated the highest recall on our data set with 95.16% and 95.45%, respectively. These models outperformed existing methods and could be incorporated into a malware detector’s file processing pipeline to filter out potentially malicious polyglots before file type-dependent feature extraction takes place.

Koch, Luke↗

Toward the Detection of Polyglot Files

Standardized file types play a key role in the development and use of computer software. However, it is possible to confound standardized file type processing by creating a file that is valid in multiple file types. The resulting polyglot (many languages) file can confuse file type identification, allowing elements of the file to evade analysis. This is especially problematic for malware detection systems that rely on file type identification for feature extraction. Although work has been done to identify file types using more comprehensive methods than file signatures, accurate identification of polyglot files remains an open problem. Since malware detection systems routinely perform file type-specific feature extraction, polyglot files need to be filtered out prior to ingestion by these systems. Otherwise, malicious content could pass through undetected. To address the problem of polyglot detection we assembled a data set using the mitra tool. We then evaluated the performance of the most commonly used file identification tools, including file, polydet, binwalk, and TrID. Our analysis demonstrates that existing file type detection tools fail to provide reliable polyglot detection. We then evaluated the ability of a range of machine and deep learning models to detect polyglot files. The most performant models were MalConv2 and Catboost, which demonstrated the highest recall on our data set with 95.16% and 95.45%, respectively. These models outperformed existing methods and could be incorporated into a malware detector’s file processing pipeline to filter out potentially malicious polyglots before file type-dependent feature extraction takes place.

Koch, Lucas↗

TU-FG-201-05: Varian MPC as a Statistical Process Control Tool

Purpose: Quality assurance in radiotherapy requires the measurement of various machine parameters to ensure they remain within permitted values over time. In Truebeam release 2.0 the Machine Performance Check (MPC) was released allowing beam output and machine axis movements to be assessed in a single test. We aim to evaluate the Varian Machine Performance Check (MPC) as a tool for Statistical Process Control (SPC). Methods: Varian’s MPC tool was used on three Truebeam and one EDGE linac for a period of approximately one year. MPC was commissioned against independent systems. After this period the data were reviewed to determine whether or not the MPC was useful as a process control tool. Analyses on individual tests were analysed using Shewhart control plots, using Matlab for analysis. Principal component analysis was used to determine if a multivariate model was of any benefit in analysing the data. Results: Control charts were found to be useful to detect beam output changes, worn T-nuts and jaw calibration issues. Upper and lower control limits were defined at the 95% level. Multivariate SPC was performed using Principal Component Analysis. We found little evidence of clustering beyond that which might be naively expected such as beam uniformity and beam output. Whilst this makes multivariate analysis of little use it suggests that each test is giving independent information. Conclusion: The variety of independent parameters tested in MPC makes it a sensitive tool for routine machine QA. We have determined that using control charts in our QA programme would rapidly detect changes in machine performance. The use of control charts allows large quantities of tests to be performed on all linacs without visual inspection of all results. The use of control limits alerts users when data are inconsistent with previous measurements before they become out of specification. A. Carver has received a speaker’s honorarium from Varian.

07 ISOTOPE AND RADIATION SOURCES↗

CyPhyR: a cyber‐physical analysis tool for measuring and enabling resiliency in microgrids

This study presents a tool to study the cyber‐physical resiliency (CyPhyR) of critical energy infrastructure system, in particular the effect of cyber attacks on the microgrid's resiliency. The developed tool enables measuring resiliency using data from cyber and physical systems and suggests control decisions for resilient planning and operation of the microgrid. The microgrid resiliency is formulated based on graph theory based indices and cyber‐power system characteristics. A Common Vulnerability Scoring System based metric called the Cyber Asset Impact Potential is developed and used in the planning phase, and another metric, Cyber Impact Severity is introduced to study the system performance in the operational phase. The information from these two phases is provided to the operator to make informed and proactive decisions to ensure the resilient operation of the microgrid. The performance of the developed tool has been tested using comprehensive real‐time cyber‐power testbed for a Consortium for Electric Reliability Technology Solutions microgrid test system.

Venkataramanan, Venkatesh↗

Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms

The emergent practical applicability of the Quantum Approximate Optimization Algorithm (QAOA) for approximate combinatorial optimization is a subject of considerable interest. One of the primary limitations of QAOA is the task of finding a set of good parameters, which is usually done using a variational optimization loop. Parameter transfer, or parameter concentration, is a phenomenon where QAOA angles trained on problem instances that are self-similar tend to perform well for other problem instances from that similar class. This suggests a potentially highly efficient and scalable non-variational learning method for QAOA angle finding. In this work, we systematically study QAOA parameter transferability from small problem sizes (16 and 27 decision variables) onto large problem instances (up to 156 qubits) for heavy-hex graph Ising models with geometrically local higher order terms using the Julia based QAOA simulation tool \texttt{JuliQAOA} to perform classical angle finding for up to $49$ QAOA layers ($p$). Parameter transfer of the fixed angles is validated using a combination of full statevector, Projected Entangled Pair States (PEPS), Matrix Product State (MPS), and LOWESA numerical simulations. We find that the QAOA parameter transfer from single instances applied to other (unseen) problem instances does not in general provide monotonically improving performance as a function of $p$ - there are many cases where the performance temporarily decreases as a function of $p$ - but despite this the transferred angles have a general trend of improved expectation value as the QAOA depth increases, in many cases converging close to the true ground-state energy of the $100+$ qubit instances. We also sample the hardware-compatible Ising models using the ensemble of transfer-learned QAOA parameters on several superconducting qubit IBM Quantum processors with 127, 133, and 156 qubits. We find continuous solution quality improvement of the hardware-compatible QAOA circuits run on the IBM NISQ processors up to $p=5$ on \texttt{ibm\_fez}, up to $p=9$ on \texttt{ibm\_torino}, and up to $p=10$ on \texttt{ibm\_pittsburgh}.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Energy Efficient Engine exhaust mixer model technology report addendum; phase 3 test program

The Phase 3 exhaust mixer test program was conducted to explore the trends established during previous Phases 1 and 2. Combinations of mixer design parameters were tested. Phase 3 testing showed that the best performance achievable within tailpipe length and diameter constraints is 2.55 percent better than an optimized separate flow base line. A reduced penetration design achieved about the same overall performance level at a substantially lower level of excess pressure loss but with a small reduction in mixing. To improve reliability of the data, the hot and cold flow thrust coefficient analysis used in Phases 1 and 2 was augmented by calculating percent mixing from traverse data. Relative change in percent mixing between configurations was determined from thrust and flow coefficient increments. The calculation procedure developed was found to be a useful tool in assessing mixer performance. Detailed flow field data were obtained to facilitate calibration of computer codes.

Larkin, M. J.↗

An Introduction to Markov Modeling: Concepts and Uses

Kharkov modeling is a modeling technique that is widely useful for dependability analysis of complex fault tolerant systems. It is very flexible in the type of systems and system behavior it can model. It is not, however, the most appropriate modeling technique for every modeling situation. The first task in obtaining a reliability or availability estimate for a system is selecting which modeling technique is most appropriate to the situation at hand. A person performing a dependability analysis must confront the question: is Kharkov modeling most appropriate to the system under consideration, or should another technique be used instead? The need to answer this gives rise to other more basic questions regarding Kharkov modeling: what are the capabilities and limitations of Kharkov modeling as a modeling technique? How does it relate to other modeling techniques? What kind of system behavior can it model? What kinds of software tools are available for performing dependability analyses with Kharkov modeling techniques? These questions and others will be addressed in this tutorial.

Boyd, Mark A.↗

Analysis Tools for CFD Multigrid Solvers

Analysis tools are needed to guide the development and evaluate the performance of multigrid solvers for the fluid flow equations. Classical analysis tools, such as local mode analysis, often fail to accurately predict performance. Two-grid analysis tools, herein referred to as Idealized Coarse Grid and Idealized Relaxation iterations, have been developed and evaluated within a pilot multigrid solver. These new tools are applicable to general systems of equations and/or discretizations and point to problem areas within an existing multigrid solver. Idealized Relaxation and Idealized Coarse Grid are applied in developing textbook-efficient multigrid solvers for incompressible stagnation flow problems.

Mineck, Raymond E.↗