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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 109 records · Page 6

Boolean differentiation and integration using Karnaugh maps

Algorithms are presented for differentiation and integration of Boolean functions by means of Karnaugh maps. The algorithms are considered simple when the number of variables is six or less; in this case Boolean differentiation and integration is said to be as easy as the Karnaugh map method of simplifying switching functions. It is suggested that the algorithms would be useful in the analysis of faults in combinational systems and in the synthesis of asynchronous sequential systems which utilize edge-sensitive flip-flops.

Tucker, J. H.↗

Synchronous Control Effort Minimized for Magnetic-Bearing-Supported Shaft

Various disturbances that are synchronous with the shaft speed can complicate radial magnetic bearing control. These include position sensor target irregularities (runout) and shaft imbalance. The method presented here allows the controller to ignore all synchronous harmonics of the shaft position input (within the closed-loop bandwidth) and to respond only to asynchronous motions. The result is reduced control effort.

Brown, Gerald V.↗

Real-time transmission of full-motion echocardiography over a high-speed data network: impact of data rate and network quality of service

With high-resolution network transmission required for telemedicine, education, and guided-image acquisition, the impact of errors and transmission rates on image quality needs evaluation. METHODS: We transmitted clinical echocardiograms from 2 National Aeronautics and Space Administration (NASA) research centers with the use of Motion Picture Expert Group-2 (MPEG-2) encoding and asynchronous transmission mode (ATM) network protocol over the NASA Research and Education Network. Data rates and network quality (cell losses [CLR], errors [CER], and delay variability [CVD]) were altered and image quality was judged. RESULTS: At speeds of 3 to 5 megabits per second (Mbps), digital images were superior to those on videotape; at 2 Mbps, images were equivalent. Increasing CLR caused occasional, brief pauses. Extreme CER and CDV increases still yielded high-quality images. CONCLUSIONS: Real-time echocardiographic acquisition, guidance, and transmission is feasible with the use of MPEG-2 and ATM with broadcast quality seen above 3 Mbps, even with severe network quality degradation. These techniques can be applied to telemedicine and used for planned echocardiography aboard the International Space Station.

NASA Discipline Cardiopulmonary↗

Coordinated frequency regulation among asynchronous AC grids with an MTDC system

With the increasing penetration level of renewable power, the power systems’ inertias are decreasing. To ensure that the frequency is above the threshold of the under frequency load shedding, one effective way is to share the spinning reserves among asynchronous AC grids through HVDC systems. In this paper, a coordinated frequency regulation scheme that enables spinning reserves sharing is proposed for such hybrid AC/DC grids. This scheme is a communication-free method that consists of the droop control, the inertia emulation control and the frequency safety control. The combined response of the three controls can increase not only the frequency nadir but also the settled frequency of the disturbed grid. In addition, the hysteresis comparators and the power injection limits are adopted in the frequency regulation scheme to reduce the coupling effect among AC grids. Thus, under small and harmless disturbance, the frequency regulation scheme will be inactive; the disturbance in strong AC grids would not affect the weak AC systems. The frequency regulation scheme coordinates well with the automatic generation control of the grids. Furthermore, the feasibility and effectiveness of the proposed frequency regulation scheme are verified through simulation studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SAGIPS: a physics-inspired scalable asynchronous generative inverse-problem solver

Abstract Solving large-scale inverse problems using deep-learning algorithms have become an essential part of modern research and industrial applications. The complexity of the underlying inverse problem may require the utilization of high performance computing systems which poses a challenge on the algorithmic design of the inverse problem solver. Most deep learning algorithms require, due to their design, custom parallelization techniques in order to be resource efficient while showing a reasonable convergence. In this paper we introduce a S calable A synchronous G enerative I nverse P roblem S olver (SAGIPS) on high-performance computing systems. We present a workflow that utilizes an asynchronous ring-allreduce algorithm to transfer the gradients of the generator network across multiple GPUs. Experiments with a scientific proxy application demonstrate that SAGIPS shows near linear weak scaling, together with a convergence quality that is comparable to traditional methods. The approach presented here allows leveraging Generative Adverserial Network across multiple GPUs, promising advancements in solving complex inverse problems at scale.

97 MATHEMATICS AND COMPUTING↗

Firearm discharge location systems and methods

Firearm discharge location systems and methods are described. According to one aspect, a firearm discharge location system includes a plurality of microphones spaced from one another, timing circuitry configured to generate a plurality of asynchronous timing references, wherein data capture operations with respect to the microphones of a first pair are synchronized with one another using a first of the timing references and data capture operations with respect to the microphones of a second pair are synchronized with one another using a second of the timing references, and processing circuitry configured to use outputs of the first and second pairs of the microphones to identify a location of a firearm discharge.

Gonzalez, Eric G.↗

The ABACUS cosmological N -body code

We present abacus, a fast and accurate cosmological N-body code based on a new method for calculating the gravitational potential from a static multipole mesh. The method analytically separates the near- and far-field forces, reducing the former to direct 1/r 2 summation and the latter to a discrete convolution over multipoles. The method achieves 70 million particle updates per second per node of the Summit supercomputer, while maintaining a median fractional force error of 10 -5 . We express the simulation time-step as an event-driven ‘pipeline’, incorporating asynchronous events such as completion of co-processor work, input/output, and network communication. abacus has been used to produce the largest suite of N-body simulations to date, the abacussummit suite of 60 trillion particles, incorporating on-the-fly halo finding. abacus enables the production of mock catalogues of the volume and resolution required by the coming generation of cosmological surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Formally Verified ZTA Requirements for OT/ICS Environments with Isabelle/HOL: Preprint

The clean energy transformation led to the integration of distributed energy resources on a top of the grid, and so a substantial increase in the complexity of power grids infrastructure and the underlying operational technology environment. Operational technology environments are becoming a system of systems, integrating heterogeneous devices which are software/hardware intensive, have ever increasing demands to exploit advances in commodity of software/hardware infrastructures, and this for good reasons - improving energy systems requirements such as cybersecurity and resilience. In such a setting, system requirements at different levels mix, thus undesirable outcomes will surely happen. The use of formal methods will remove ambiguity, increase automation and provide high levels of assurance and reliability. In this paper, we contribute a methodology and a framework for the system level verification of zero trust architecture requirements in operational technology environments. We define a formal specification for the core functionalities of operational technology environments, the corresponding invariants, and security proofs. Of particular note is our modular approach for the formal verification of asynchronous interactions in operational technology environments. The formal specification and the proofs have been mechanized using the interactive theorem proving environment Isabelle/HOL.

formal methods↗

Formally Verified ZTA Requirements for OT/ICS Environments with Isabelle/HOL

The clean energy transformation includes the integration of distributed energy resources with the power grid, which has led to a substantial increase in the complexity of power grids infrastructure and the underlying operational technology environment. Power grids infrastructure represents an operational technology environment that has become a system of systems, integrating heterogeneous devices which are both software-and hardware-intensive; as a result, there are increasing demands to exploit advances in the commodity of software-hardware infrastructures to improve energy systems requirements such as cybersecurity and resilience. In such a setting, system requirements at different levels mix, which leads to vulnerabilities and undesirable outcomes. The use of formal methods to characterize and prove system requirements removes ambiguity, increases automation, and provides high levels of assurance and reliability. In this paper, we contribute a methodology and a framework for the system-level verification of zero trust architecture requirements in operational technology environments. We define a formal specification for the core functionalities of operational technology environments, the corresponding invariants, and security proofs. Of particular note is our modular approach for the formal verification of asynchronous interactions in operational technology environments. The formal specification and the proofs have been mechanized using the interactive theorem proving environment Isabelle/HOL.

formal methods↗

Deforestation reshapes land-surface energy-flux partitioning

Land-use and land-cover change significantly modify local land-surface characteristics and water/energy exchanges, which can lead to atmospheric circulation and regional climate changes. In particular, deforestation accounts for a large portion of global land-use changes, which transforms forests into other land cover types, such as croplands and grazing lands. Many previous efforts have focused on observing and modeling land–atmosphere–water/energy fluxes to investigate land–atmosphere coupling induced by deforestation. However, interpreting land–atmosphere–water/energy-flux responses to deforestation is often complicated by the concurrent impacts from shifts in land-surface properties versus background atmospheric forcings. In this study, we used 29 paired FLUXNET sites, to improve understanding of how deforested land surfaces drive changes in surface-energy-flux partitioning. Each paired sites included an intact forested and non-forested site that had similar background climate. We employed transfer entropy, a method based on information theory, to diagnose directional controls between coupling variables, and identify nonlinear cause–effect relationships. Transfer entropy is a powerful tool to detective causal relationships in nonlinear and asynchronous systems. The paired eddy covariance flux measurements showed consistent and strong information flows from vegetation activity (gross primary productivity (GPP)) and physical climate (e.g. shortwave radiation, air temperature) to evaporative fraction (EF) over both non-forested and forested land surfaces. More importantly, the information transfers from radiation, precipitation, and GPP to EF were significantly reduced at non-forested sites, compared to forested sites. We then applied these observationally constrained metrics as benchmarks to evaluate the Energy Exascale Earth System Model (E3SM) land model (ELM). ELM predicted vegetation controls on EF relatively well, but underpredicted climate factors on EF, indicating model deficiencies in describing the relationships between atmospheric state and surface fluxes. Moreover, changes in controls on surface energy flux partitioning due to deforestation were not detected in the model. We highlight the need for benchmarking model simulated surface-energy fluxes and the corresponding causal relationships against those of observations, to improve our understanding of model predictability on how deforestation reshapes land surface energy fluxes.

54 ENVIRONMENTAL SCIENCES↗

Customized Bayesian optimization for efficient beam tuning at the facility for rare isotope beams

Bayesian optimization (BO) has recently emerged as a powerful approach for on-line beam tuning, and it is rapidly gaining adoption across accelerator facilities due to its flexibility and efficiency in handling complex optimization tasks. At the Facility for Rare Isotope Beams, rapid and reliable tuning is essential to support the delivery of diverse ion species. To improve the practicality of BO in this setting, we implemented several enhancements, including scalarized composite objective construction for multicriteria optimization, asynchronous evaluation for better resource utilization, prior-mean-assisted optimization to accelerate convergence, and a local search strategy for rapid completion of the task. We present the details of these methods, discuss challenges-encountered, and share our experience applying them to specific beam-tuning tasks.

Accelerators & storage rings↗

Using Pipelined XNOR Logic to Reduce SEU Risks in State Machines

Single-event upsets (SEUs) pose great threats to avionic systems state machine control logic, which are frequently used to control sequence of events and to qualify protocols. The risks of SEUs manifest in two ways: (a) the state machine s state information is changed, causing the state machine to unexpectedly transition to another state; (b) due to the asynchronous nature of SEU, the state machine's state registers become metastable, consequently causing any combinational logic associated with the metastable registers to malfunction temporarily. Effect (a) can be mitigated with methods such as triplemodular redundancy (TMR). However, effect (b) cannot be eliminated and can degrade the effectiveness of any mitigation method of effect (a). Although there is no way to completely eliminate the risk of SEU-induced errors, the risk can be made very small by use of a combination of very fast state-machine logic and error-detection logic. Therefore, one goal of two main elements of the present method is to design the fastest state-machine logic circuitry by basing it on the fastest generic state-machine design, which is that of a one-hot state machine. The other of the two main design elements is to design fast error-detection logic circuitry and to optimize it for implementation in a field-programmable gate array (FPGA) architecture: In the resulting design, the one-hot state machine is fitted with a multiple-input XNOR gate for detection of illegal states. The XNOR gate is implemented with lookup tables and with pipelines for high speed. In this method, the task of designing all the logic must be performed manually because no currently available logic synthesis software tool can produce optimal solutions of design problems of this type. However, some assistance is provided by a script, written for this purpose in the Python language (an object-oriented interpretive computer language) to automatically generate hardware description language (HDL) code from state-transition rules.

Le, Martin↗

SVM-Based Synchronized Fault Detection for 100% Renewable Microgrids

Traditional protection schemes face significant challenges when applied to microgrids with high penetrations of renewables with inverter-based resources (IBRs). The proliferation of advanced sensing and communication technologies has generated copious data, offering an opportunity to overcome these limitations using data-driven machine learning approaches. This work proposes a novel approach based on a support vector machine (SVM) for detecting faults within a 100% renewable microgrid. The approach encompasses a systematic offline training stage for the development of a linear SVM-based fault detection algorithm. This process covers offline data collection from the microgrid under study, the extraction of features such as positive- and negative-sequence components and the total harmonic distortion of the voltage and current measurements of the relays, and the design of the linear SVM-based classifier. During the online implementation, however, different classifiers can exhibit asynchronicity in detecting the fault inception at different subcycle-to-cycle period-level delays. To circumvent this asynchronicity issue, a separate algorithm is developed for each relay to estimate the fault inception time as close to the real fault time. The performance of the proposed SVM-based synchronized fault detection method is evaluated using online time-domain simulation studies on a microgrid test system. The results corroborate the reliability of the fault detection scheme when tested under various fault cases (fault types, locations, and impedances) and non-fault cases during both grid-tied and islanded operation modes.

100% microgrid↗

SVM-Based Synchronized Fault Detection for 100% Renewable Microgrids: Preprint

Traditional protection schemes face significant challenges when applied to microgrids with high penetrations of renewables with inverter-based resources (IBRs). The proliferation of advanced sensing and communication technologies has generated copious data, offering an opportunity to overcome these limitations using data-driven machine learning approaches. This work proposes a novel approach based on a support vector machine (SVM) for detecting faults within a 100% renewable microgrid. The approach encompasses a systematic offline training stage for the development of a linear SVM-based fault detection algorithm. This process covers offline data collection from the microgrid under study, the extraction of features such as positive- and negative-sequence components and the total harmonic distortion of the voltage and current measurements of the relays, and the design of the linear SVM-based classifier. During the online implementation, however, different classifiers can exhibit asynchronicity in detecting the fault inception at different subcycle-to-cycle period-level delays. To circumvent this asynchronicity issue, a separate algorithm is developed for each relay to estimate the fault inception time as close to the real fault time. The performance of the proposed SVM-based synchronized fault detection method is evaluated using online time-domain simulation studies on a microgrid test system. The results corroborate the reliability of the fault detection scheme when tested under various fault cases (fault types, locations, and impedances) and non-fault cases during both grid-tied and islanded operation modes.

100% microgrid↗

Cascaded clocks measurement and simulation findings

This paper will examine aspects related to network synchronization distribution and the cascading of timing elements. Methods of timing distribution have become a much debated topic in standards forums and among network service providers (both domestically and internationally). Essentially these concerns focus on the need to migrate their existing network synchronization plans (and capabilities) to those required for the next generation of transport technologies (namely, the Synchronous Digital Hierarchy (SDH), Synchronous Optical Networks (SONET), and Asynchronous Transfer Mode (ATM). The particular choices for synchronization distribution network architectures are now being evaluated and are demonstrating that they can indeed have a profound effect on the overall service performance levels that will be delivered to the customer. The salient aspects of these concerns reduce to the following: (1) identifying that the devil is in the details of the timing element specifications and the distribution of timing information (i.e., small design choices can have a large performance impact); (2) developing a standardized method of performance verification that will yield unambiguous results; and (3) presentation of those results. Specifically, this will be done for two general cases: an ideal input, and a noisy input to a cascaded chain of slave clocks.

Chislow, Don↗

BARC Element Classifier (barc)

SAND2024-02120O This program enumerates and classifies all possible functional elements in several different categories within the Ballistic Asynchronous Reversible Computing (barc) model of computation. barc software is a research tool that is being used to help document the possible digital behaviors of primitive functional elements in the ABRC a.k.a. BARC model of computation. The method of operation of this software leverages elementary concepts and methods from discrete mathematics: combinatorics (permutations), partitions and equivalence classes, symmetry transformations, and the theory of finite groups. Implementation is in Python programming language. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Frank, Michael↗

Electrode strain dynamics in layered intercalation battery cathodes

Rechargeable batteries using electrodes based on intercalation chemistry exhibit notable cyclability, yet their performance still suffers from chemomechanical degradation. In this study, by combining a suite of operando microscopy methods, we explored electrode strain evolution and observed intricate particle cluster rearrangement under electrochemical stimuli. We show that early-stage strain accumulation in intercalation cathodes occurs during the period of interparticle charge transfer and redox reactions stemming from asynchronous coupling and decoupling between chemical (de)intercalation and physical grain motion. This interplay drives heterogeneous redox activity, localized charge equilibration, and multiscale strain cascades that propagate through an asynchronous network of chemical-mechanical interactions. Together, these findings reveal how collective particle dynamics and hierarchical strain transmission dictate electrode deformation and degradation in intercalation cathodes.

25 ENERGY STORAGE↗

A software architecture for multidisciplinary applications: Integrating task and data parallelism

Data parallel languages such as Vienna Fortran and HPF can be successfully applied to a wide range of numerical applications. However, many advanced scientific and engineering applications are of a multidisciplinary and heterogeneous nature and thus do not fit well into the data parallel paradigm. In this paper we present new Fortran 90 language extensions to fill this gap. Tasks can be spawned as asynchronous activities in a homogeneous or heterogeneous computing environment; they interact by sharing access to Shared Data Abstractions (SDA's). SDA's are an extension of Fortran 90 modules, representing a pool of common data, together with a set of Methods for controlled access to these data and a mechanism for providing persistent storage. Our language supports the integration of data and task parallelism as well as nested task parallelism and thus can be used to express multidisciplinary applications in a natural and efficient way.

Chapman, Barbara↗