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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 19 records

Real-Time Considerations for Rugged Embedded Systems

This chapter introduces the characterizing aspects of embedded systems, and discusses the specific features that a designer should address to an embedded system “rugged”, i.e., able to operate reliably in harsh environments. The chapter addresses both the hardware and the less obvious software aspect. After presenting a current list of certifications for ruggedization, the chapters present a case study that focuses on the interaction of the hardware and software layers in reactive real-time system. In particular, it shows how the use of fast FPGA prototyping could provide insights on unexpected factors that influence the performance and thus responsiveness to events of a scheduling algorithm for multiprocessor systems that manages both periodic, hard real-time task, and aperiodic tasks. The main lesson is that to make the system “rugged”, a designer should consider these issues by, for example, overprovisioning resources and/or computation capabilities.

FPGA↗

Combined Force-Frequency Sampling for Simulation of Systems Having Rugged Free Energy Landscapes.

An adaptive, machine learning-based sampling method is presented for simulation of systems having rugged, multidimensional free energy landscapes. The method's main strength resides in its ability to learn both from the frequency of visits to distinct states and the generalized force estimates that arise in a system as it evolves in phase space. This is accomplished by introducing a self-integrating artificial neural network, which generates an estimate of the free energy directly from its derivatives. The usefulness of the proposed combined approach is examined in the context of two concrete examples, namely, an alanine dipeptide molecule in water and a polymer diffusing through a narrow pore. This new method is found to be robust, faster, and more accurate than approaches that rely only on frequency-based or generalized force-based estimations. After combining the proposed approach with overfill protection and support for sparse data storage and training, the method is shown to be more effective than comparable, previously available techniques and capable of scaling efficiently to larger numbers of collective variables.

Sevgen, Emre↗

Novel and Rugged Electromagnetic Wireless System for Long-Term Subsurface CO₂ Plume Monitoring and Saturation Mapping

Novel and rugged electromagnetic wireless system for long-term subsurface CO₂ plume monitoring and saturation mapping is a Phase I SBIR project led by Cyentech Consulting LLC to develop a permanently installed, outside-casing electromagnetic monitoring system for long-term carbon storage monitoring. The project addresses a major challenge in carbon capture and storage: the need for reliable, cable-free downhole monitoring that can detect CO₂ plume movement and saturation changes without compromising well integrity through casing perforations or external umbilical cables.

58 GEOSCIENCES↗

Estimating the density of states of frustrated spin systems

Abstract Estimating the density of states (DOS) of systems with rugged free energy landscapes is a notoriously difficult task of the utmost importance in many areas of physics ranging from spin glasses to biopolymers. DOS estimation has also recently become an indispensable tool for the benchmarking of quantum annealers when these function as samplers. Some of the standard approaches suffer from a spurious convergence of the estimates to metastable minima, and these cases are particularly hard to detect. Here, we introduce a sampling technique based on population annealing enhanced with a multi-histogram analysis and report on its performance for spin glasses. We demonstrate its ability to overcome the pitfalls of other entropic samplers, resulting in some cases in large scaling advantages that can lead to the uncovering of new physics. The new technique avoids some inherent difficulties in established approaches and can be applied to a wide range of systems without relevant tailoring requirements. Benchmarking of the studied techniques is facilitated by the introduction of several schemes that allow us to achieve exact counts of the degeneracies of the tested instances.

Barash, Lev (ORCID:000000022298785X)↗

Novel Compact Ceilometer (Final Scientific-Technical Report)

Fibertek is developing a novel ceilometer system that provides a new measurement capability not currently available to weather stations such as those in the Department of Energy's AmeriFlux network. Commercially available instruments do not have the sensitivity to see atmospheric aerosols. If the atmospheric aerosols can be measured, then the altitude of the boundary layer can be determined from a discontinuity in the aerosol concentration. The altitude of the boundary layer is a critical parameter in climate and weather models, and adding this piece of information will greatly improve the accuracy of these models. Fibertek's design provides this capability in an inexpensive robust fieldable instrument by applying a new sensor technology: the Silicon Photomultiplier (SiPM). SiPMs are called "photomultipliers" in that they provide very similar performance as a traditional photomultiplier including single photon sensitivity and linear response. However, they are a completely different technology which offers several advantages. They are small, inexpensive, solid-state, and extremely robust. They do not require cooling. They operate at much lower voltages. They cannot be damaged by inadvertent reflections, and when saturated they recover in less than a microsecond, so they don't need to be shielded from the outgoing laser pulse. In short, they make single photon sensitivity accessible for an inexpensive, simple, rugged, fieldable system. In this Phase 1 effort Fibertek developed a breadboard version of the ceilometer to demonstrate the feasibility of our approach. Our partner, Penn State, conducted atmospheric measurements to validate the lidar’s performance and determine algorithms for automatically identifying the height of the boundary layer. The lidar shows sufficient sensitivity to fully characterize the boundary layer in clear air daytime and nighttime conditions.

47 OTHER INSTRUMENTATION↗

Adaptive enhanced sampling by force-biasing using neural networks

A machine learning assisted method is presented for molecular simulation of systems with rugged free energy landscapes. The method is general and can be combined with other advanced sampling techniques. In the particular implementation proposed here, it is illustrated in the context of an adaptive biasing force approach where, rather than relying on discrete force estimates, one can resort to a self-regularizing artificial neural network to generate continuous, estimated generalized forces. By doing so, the proposed approach addresses several shortcomings common to adaptive biasing force and other algorithms. Specifically, the neural network enables smooth estimates of generalized forces in sparsely sampled regions, force estimates in previously unexplored regions, and continuous force estimates with which to bias the simulation, as opposed to biases generated at specific points of a discrete grid. The usefulness of the method is illustrated with three different examples, chosen to highlight the wide range of applicability of the underlying concepts. In all three cases, the new method is found to enhance considerably the underlying traditional adaptive biasing force approach. Furthermore, the method is also found to provide improvements over previous implementations of neural network assisted algorithms.

97 MATHEMATICS AND COMPUTING↗

Particulate mass migration and mixing in cylindrically contained explosions

Abstract To explore particulate movement near the plasma of chemical explosions, rugged tracer particles were placed within and on the exterior of metal charges and electrically detonated. The particles were collected on/in the porous walls of plastic cylinders at diameters that correlated to the plasma width during different phases of the explosion. The particles’ positions were determined by Boolean logic analysis of their luminescent intensity. The cylinders which caught particles from the initial phases of the explosion retained placement information, while wider cylinders showed uniform mixing. These results/analysis methodology can help improve the understanding of particulate mixing in harsh environments. Graphical abstract

36 MATERIALS SCIENCE↗

Layered nested Markov chain Monte Carlo

A configurational sampling algorithm based on nested layerings of Markov chains (Layered Nested Markov Chain Monte Carlo or L-NMCMC) is presented for simulations of systems characterized by rugged free energy landscapes. The layerings are generated using a set of auxiliary potential energy surfaces. The implementation of the method is demonstrated in the context of a rugged, two-dimensional potential energy surface. The versatility of the algorithm is next demonstrated on a simple, many body system, namely, a canonical Lennard-Jones fluid in the liquid state. In that example, different layering schemes and auxiliary potentials are used, including variable cutoff distances and excluded volume tempering. In addition to calculating a variety of properties of the system, it is also shown that L-NMCMC, when combined with a free-energy perturbation formalism, provides a straightforward means to construct approximate free-energy surfaces at no additional computational cost using the sampling distributions of each auxiliary Markov chain. In conclusion, the proposed L-NMCMC scheme is general in that it could be complementary to any number of methods that rely on sampling from a target distribution or methods that exploit a hierarchy of time scales and/or length scales through decomposition of the potential energy.

97 MATHEMATICS AND COMPUTING↗

Spectral Advanced Radiological Computer System Applications

The Spectral Advanced Radiological Computer System (SPARCS) is a versatile, rugged, multi-platform radiation detection system. It is an easy-to-install and easy-to-operate, gamma radiation detection system for radiological emergency response. It has been designed and built on a foundation of mobile and aerial detection experience that spans four decades. This article reviews the scope and operational thrust of the SPARCS, making references to the versatility and capability of the system and its application under various threat conditions. SPARCS is a multiplatform global gamma ray detection system used at the international level.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Demonstration of improved dilution tolerance using a production-intent compact nanosecond pulse ignition system

Transient plasma ignition using nanosecond pulses has demonstrated the potential to enable improved fuel economy and reduced emissions by enabling lean and EGR limit extension in dilute burn engines. Existing spark ignition technology is not adequate because the energy transfer mechanisms between the spark and the fuel-air mixture are not efficient enough to guarantee stable ignition for dilute mixtures at high-load conditions. Additionally, long duration sparks and other advanced ignition solutions that require increased energy delivered accelerate spark plug electrode wear. To date, non-thermal plasma ignition with nanosecond pulses have demonstrated a lean ignition limit beyond an air/fuel ratio of 24 [1], demonstrated high-pressure ignition at densities equivalent to over 100 bar at the time of ignition [2], and demonstrated stable (COV <3 %) ignition at EGR dilution levels >20 % [3]. While low-energy nanosecond pulses have demonstrated strong performance compared to existing solutions, they currently only exist on the market in laboratory systems, rather than a production ready system in a single rugged, weather-proof, under-the-hood enclosure. Transient Plasma Systems (TPS) has recently demonstrated the potential for a retroffitable solution similar to coil-on-plug architecture that allows a direct replacement of existing ignition technology without any engine modification. The system was run on a gasoline direct injection engine at Argonne National Laboratory and demonstrated the same trends as previously observed with research grade systems, including lean and EGR limit extension and more stable ignition across a range of loads. The system was capable of delivering 30 kV pulses in bursts of up to 20 pulses at 30 kHz, and demonstrated stable combustion at an air/fuel ratio of 23.5, exhaust gas recirculation of 23 %, and ignition at 19.2 bar with COV <3 % using only 20 kV pulses.

nanosecond pulsed power↗

Learning the ground state of a non-stoquastic quantum Hamiltonian in a rugged neural network landscape

Strongly interacting quantum systems described by non-stoquastic Hamiltonians exhibit rich low-temperature physics. Yet, their study poses a formidable challenge, even for state-of-the-art numerical techniques. Here, we investigate systematically the performance of a class of universal variational wave-functions based on artificial neural networks, by considering the frustrated spin- 1/2 1 / 2 J_1-J_2 J 1 − J 2 Heisenberg model on the square lattice. Focusing on neural network architectures without physics-informed input, we argue in favor of using an ansatz consisting of two decoupled real-valued networks, one for the amplitude and the other for the phase of the variational wavefunction. By introducing concrete mitigation strategies against inherent numerical instabilities in the stochastic reconfiguration algorithm we obtain a variational energy comparable to that reported recently with neural networks that incorporate knowledge about the physical system. Through a detailed analysis of the individual components of the algorithm, we conclude that the rugged nature of the energy landscape constitutes the major obstacle in finding a satisfactory approximation to the ground state wavefunction, and prevents learning the correct sign structure. In particular, we show that in the present setup the neural network expressivity and Monte Carlo sampling are not primary limiting factors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Rapid changes in agricultural land use and hydrology in the Driftless Region

Annual cropping systems are common in the Driftless Region of the U.S. Midwest, but soil degradation is prone to happen in such systems due to the rugged topography of the region. Recent rapid increases in row crop area have been noted in this region, with annual precipitation and hydrologic extremes on the rise in recent decades. The aim of this research to use geospatial datasets and tools in order to assess the regional trends in land use, precipitation, and hydrologic change and quantify the relationship between these environmental trends. Between 2006 and 2017, substantial row crop expansion of 10,000 ha or more was common across HUC 8 (Hydrologic Unit Code 8) watersheds in our study area. Expansion occurred mainly on steeper slopes, converting existing grasslands or alfalfa (Medicago sativa L.) to row crops. Classifying land as planted (in row crops), plantable (in row crops or could be converted), and unplantable (unable to be converted) revealed that Driftless Region watersheds have ~30–50% of plantable land available for future expansion. Annual precipitation was highly variable during this time period but had a general increasing trend. On average, precipitation showed higher correlation to streamflow compared to row crop expansion across 27 USGS river gage drainage basins in our study area. However, when the increase in row crop area was significant and was accompanied by increasing precipitation, stronger correlation between row crop area and annual streamflow was exhibited. This finding suggests that row crop expansion acts to enhance the effects of increasing precipitation on local hydrology.

54 ENVIRONMENTAL SCIENCES↗

Gamma-Ray Simulated Spectrum Deconvolution of a LaBr₃ 1-in. x 1-in. Scintillator for Nondestructive ATR Fuel Burnup On-Site Predictions

A deconvolution method for a LaBr₃ 1"x1" detector for nondestructive Advanced Test Reactor (ATR) fuel burnup applications was developed. The method consisted of obtaining the detector response function, applying a deconvolution algorithm to 1”x1” LaBr₃ simulated, data along with evaluating the effects that deconvolution have on nondestructively determining ATR fuel burnup. The simulated response function of the detector was obtained using MCNPX as well with experimental data. The Maximum-Likelihood Expectation Maximization (MLEM) deconvolution algorithm was selected to enhance one-isotope source-simulated and fuel- simulated spectra. The final evaluation of the study consisted of measuring the performance of the fuel burnup calibration curve for the convoluted and deconvoluted cases. The methodology was developed in order to help design a reliable, high resolution, rugged and robust detection system for the ATR fuel canal capable of collecting high performance data for model validation, along with a system that can calculate burnup and using experimental scintillator detector data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Performance Evaluation of an Intelligent Sensor Platform for Radiation Monitoring Applications

Accurate, rugged, and reliable radiation detection systems are important for area and environmental monitoring applications. The desire for spectroscopic capability has increased in monitoring aspects of the nuclear fuel cycle to provide fast characterization of the radiation profile of a situation, such as the planned or unplanned release of material. The reduction or elimination of having to conduct sampling for laboratory analysis can result in significant cost savings for an industry, government agency, or regulatory body. A new system, comprised of a NaI:Tl scintillator and a G-M tube, has been designed and tested, taking into account the following end-user requirements: ease-of-use, capability to network and supervise multiple units, compact form factor, low power consumption, versatility, and stability. The detector sizes were selected to accommodate a dose rate up to 1 Sv/hr. Several algorithms and analysis routines have been developed to incorporate these key needs without sacrificing on accuracy, dynamic range, nuclide identification, and sensitivity. This presentation will introduce the major hardware and software components of the platform, as well as the user interface and data analysis workflow. Key features of the hardware include an environmentally robust housing, low power signal processing electronics, patented LED-based gain stabilization, and an embedded processor for unattended instrument management and data analysis. New and improved algorithms for determining scintillator gamma dose rates, total integrated dose, and nuclide identification will be introduced. The two detector elements were modeled with MCNP and validated experimentally. The results of the radiological testing shall be presented including energy resolution, throughput, dose response, and minimum detectable activities. The dose response has been evaluated in simulations and with measurements to ensure accurate response with respect to energy spectrum of the dose field and direction of the incident radiation. Spectroscopy evaluations, such as nuclide detection probability and false alarm rates, were performed and comparisons to existing algorithms shall also be presented. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Contributed Review: The feasibility of a fully miniaturized magneto-optical trap for portable ultracold quantum technology

Experiments using laser cooled atoms and ions show real promise for practical applications in quantum-enhanced metrology, timing, navigation, and sensing as well as exotic roles in quantum computing, networking, and simulation. The heart of many of these experiments has been translated to microfabricated platforms known as atom chips whose construction readily lend themselves to integration with larger systems and future mass production. To truly make the jump from laboratory demonstrations to practical, rugged devices, the complex surrounding infrastructure (including vacuum systems, optics, and lasers) also needs to be miniaturized and integrated. In this paper we explore the feasibility of applying this approach to the Magneto-Optical Trap; incorporating the vacuum system, atom source and optical geometry into a permanently sealed micro-litre system capable of maintaining 10{sup −10} mbar for more than 1000 days of operation with passive pumping alone. We demonstrate such an engineering challenge is achievable using recent advances in semiconductor microfabrication techniques and materials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Implementation of Augmented Teleautonomy on a Hydraulic Manipulator for Nuclear Facility D and D - 19602

Robotic and remote system have been used in nuclear applications to keep the human workers from high radiation environment and enhance task performance. However, applications in the more unstructured nuclear environments present more formidable challenges to robotics and remote systems. In particular, remote operation tasks for nuclear facility D and D (or dismantling) requires dexterous manipulation of heavy objects with simple and rugged robotic equipment. To address such challenge, this paper presents a new teleoperation method of augmented teleautonomy for remote operation of tools for D and D tasks. Rather than imposing complex functionalities on the slave robot, focused innovation is directed to providing effective operator aids in such a way as to draw more performance out of human operators. In this regard, the development entails the implementation of an enhanced telerobotic operation method by incorporating multi-modal augmented reality operator aids and autonomous motion primitives. This paper presents the relevant technology development utilizing a mixed-reality telerobotic test bed, and system integration and demonstration with a rugged, hydraulic slave robot system. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Using Dark Fiber and Distributed Acoustic Sensing to Characterize a Geothermal System in the Imperial Valley, Southern California

The Imperial Valley, CA, is a tectonically active transtensional basin located south of the Salton Sea; the area hosts numerous geothermal fields, including significant hidden hydrothermal resources without surface manifestations. Development of inexpensive, rugged, and highly sensitive exploration techniques for undiscovered geothermal systems is critical for accelerating geothermal power deployment as well as unlocking a low-carbon energy future. We present a case study utilizing distributed acoustic sensing (DAS) and ambient noise interferometry for geothermal reservoir imaging, utilizing unlit fiber-optic telecommunication infrastructure (dark fiber). The study exploits two days of passive DAS data acquired in early November 2020 over a ~28-km section of fiber from Calipatria, CA to Imperial, CA. We apply ambient noise interferometry to retrieve coherent signals from DAS records and develop a bin stacking technique to attenuate the effects from persistent localized noise sources and to enhance retrieval of coherent surface waves. As a result, we are able to obtain high-resolution two-dimensional (2D) S wave velocity ($V_s$) structure to 3 km depth, based on joint inversion of both the fundamental and higher overtones. We observe a previously unmapped high $V_s$ and low $V_p$/$V_s$ ratio feature beneath the Brawley geothermal system, which we interpret to be a zone of hydrothermal mineralization and lower porosity. This interpretation is consistent with a host of other measurements including surface heat flow, gravity anomalies, and available borehole wireline data. These results demonstrate the potential utility of DAS deployed on dark fiber for geothermal system exploration and characterization in the appropriate geological settings.

Vp/Vs imaging↗