Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “heterogeneities”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 739 records · Page 41

Experimental Fuel Consumption Results from a Heterogeneous Four-Truck Platoon

Platooning has the potential to reduce greenhouse gas missions of heavy-duty vehicles. Prior platooning studies have chiefly focused on the fuel economy characteristics and three-truck platoons, and most have investigated aerodynamically homogeneous platoons with trucks of the same trim. For real world application and accurate return on investment for potential adopters, non-uniform platoons and the impacts of grade and disturbances on a platoon’s fuel economy must also be characterized. This study investigates the fuel economy of a heterogeneous four-truck platoon on a closed test track. Tests were run for one hour at a speed of 45 mph. The trucks used for this study are two 2015 Peterbilt 579’s with a Cummins ISX15 and a Paccar MX-13, and two 2009 Freightliner M915A5’s, one armored and the other unarmored. Many analysis methodologies were leveraged to describe and compare the fuel data, including lap-wise and track-segment analysis. The methodology for dividing the data into laps is described in detail. The influence of other factors beyond the aerodynamics of platooning is discussed. CAN fuel rate analysis showed excellent agreement with previous experimental trends for two and three-truck platoons. In general, the indicated fuel economy benefits in this study were 5-11% for following vehicles and 0-4% for the lead vehicle in platoon relative to their baseline fuel consumption. On a cumulative basis, all platoons saved fuel, ranging from 6% to 8% versus the sum of the standalone trucks’ fuel consumption. The practical implications of the fuel economy results are discussed, as well as avenues for future research. Introduction and Motivation platooning is controlled coordination of two or more vehicles in a convoy, sometimes called CACC (Coordinated or Cooperative Adaptive Cruise Control). The distance between vehicles in a platoon can be controlled tightly at no additional fatigue to the driver. Platooning vehicles can also respond quickly to braking events of the leader, much more quickly than the typical human driver’s reaction time of 1-1.5 s. Therefore, vehicles in a platoon can follow each other much more closely than would usually be considered a safe following distance under human operation. It is implied that under very close following conditions, platooning technology must be extremely robust before it is safe for wide-scale implementation. Platooning is under investigation as a fuel-saving technology. Close-following significantly reduces aerodynamic drag for both leading and trailing vehicles. According to the NRC in 2010, aerodynamic drag represents roughly half of a Class-8 truck’s on-highway fuel usage, meaning a 20% reduction in drag roughly equals a 10% reduction in fuel usage, if all other sources of energy loss remain equal (i.e. accessory, rolling resistance, drivetrain, braking). It is by aerodynamics that platooning saves fuel. At risk of oversimplifying the aerodynamics, following (or trailing) vehicles experience reduced wind velocity due to shielding, and the leading vehicles experience an increased aft pressure, especially at distances closer than 75’ (23 m).

greenhouse gas emissions, truck platoon, heavy-dut↗

Packaging HEP Heterogeneous Mini-apps for Portable Benchmarking and Facility Evaluation on Modern HPCs

High Energy Physics (HEP) experiments are making increasing use of GPUs and GPU dominated High Performance Computer facilities. Both the software and hardware of these systems are rapidly evolving, creating challenges for experiments to make informed decisions as to where they wish to devote resources. In its first phase, the High Energy Physics Center for Computational Excellence (HEP-CCE) produced portable versions of a number of heterogeneous HEP mini-apps, such as \ptor, FastCaloSim, Patatrack and the WireCell Toolkit, that exercise a broad range of GPU characteristics, enabling cross platform and facility benchmarking and evaluation. However, these mini-apps still require a significant amount of manual intervention to deploy on a new facility. We present our work in developing turn-key deployments of these mini-apps, where by means of containerization and automated configuration and build techniques such as Spack, we are able to quickly test new hardware, software, environments and entire facilities with minimal user intervention, and then track performance metrics over time.

Atif, Mohammad [Brookhaven] (ORCID:000000026889770↗

Watershed zonation through hillslope clustering for tractably quantifying above- and below-ground watershed heterogeneity and functions

Abstract. In this study, we develop a watershed zonation approach for characterizing watershed organization and functions in a tractable manner by integrating multiple spatial data layers. We hypothesize that (1) a hillslope is an appropriate unit for capturing the watershed-scale heterogeneity of key bedrock-through-canopy properties and for quantifying the co-variability of these properties representing coupled ecohydrological and biogeochemical interactions, (2) remote sensing data layers and clustering methods can be used to identify watershed hillslope zones having the unique distributions of these properties relative to neighboring parcels, and (3) property suites associated with the identified zones can be used to understand zone-based functions, such as response to early snowmelt or drought and solute exports to the river. We demonstrate this concept using unsupervised clustering methods that synthesize airborne remote sensing data (lidar, hyperspectral, and electromagnetic surveys) along with satellite and streamflow data collected in the East River Watershed, Crested Butte, Colorado, USA. Results show that (1) we can define the scale of hillslopes at which the hillslope-averaged metrics can capture the majority of the overall variability in key properties (such as elevation, net potential annual radiation, and peak snow-water equivalent – SWE), (2) elevation and aspect are independent controls on plant and snow signatures, (3) near-surface bedrock electrical resistivity (top 20 m) and geological structures are significantly correlated with surface topography and plan species distribution, and (4) K-means, hierarchical clustering, and Gaussian mixture clustering methods generate similar zonation patterns across the watershed. Using independently collected data, we show that the identified zones provide information about zone-based watershed functions, including foresummer drought sensitivity and river nitrogen exports. The approach is expected to be applicable to other sites and generally useful for guiding the selection of hillslope-experiment locations and informing model parameterization.

58 GEOSCIENCES↗

HAMR - Heterogeneous Accelerator Memory Resource (HAMR) v1.0

HAMR is a library defining an accelerator technology agnostic memory model that bridges between accelerator technologies (CUDA, HIP, ROCm, OpenMP, Sycl, OpenCL, Kokos, etc) and traditional CPUs in heterogeneous computing environments. HAMR is light weight and implemented in modern C++. HAMR can be used to manage memory with in a single code or as a data model for coupling codes in a technologically agnostic way. HAMR provides a Python module for coupling C++ and Python codes which implements zero-copy data transfers to and from Python using the Numpy array interface and Numba CUDA array interface protocols.

Loring, Burlen↗

Conformational heterogeneity of the BTK PHTH domain drives multiple regulatory states

Full-length Bruton’s tyrosine kinase (BTK) has been refractory to structural analysis. The nearest full-length structure of BTK to date consists of the autoinhibited SH3–SH2–kinase core. Precisely how the BTK N-terminal domains (the Pleckstrin homology/Tec homology [PHTH] domain and proline-rich regions [PRR] contain linker) contribute to BTK regulation remains unclear. We have produced crystals of full-length BTK for the first time but despite efforts to stabilize the autoinhibited state, the diffraction data still reveal only the SH3–SH2–kinase core with no electron density visible for the PHTH–PRR segment. Cryo-electron microscopy (cryoEM) data of full-length BTK, on the other hand, provide the first view of the PHTH domain within full-length BTK. CryoEM reconstructions support conformational heterogeneity in the PHTH–PRR region wherein the globular PHTH domain adopts a range of states arrayed around the autoinhibited SH3–SH2–kinase core. On the way to activation, disassembly of the SH3–SH2–kinase core opens a new autoinhibitory site on the kinase domain for PHTH domain binding that is ultimately released upon interaction of PHTH with phosphatidylinositol (3,4,5)-trisphosphate. Membrane-induced dimerization activates BTK and we present here a crystal structure of an activation loop swapped BTK kinase domain dimer that likely represents the conformational state leading to trans-autophosphorylation. Together, these data provide the first structural elucidation of full-length BTK and allow a deeper understanding of allosteric control over the BTK kinase domain during distinct stages of activation.

59 BASIC BIOLOGICAL SCIENCES↗

Heterogeneity effects on nondestructive assay measurements of enrichment in UF 6 cylinders

A set of measurements were performed using multiple mechanically cooled HPGe detectors at six positions around a cylinder uranium hexafluoride to assess if matrix inhomogeneity is detectible and effects the determined apparent uranium enrichment. These measurements were performed on nine 30B cylinders of uranium hexafluoride. Six of the cylinders appeared to be homogeneous and had similar apparent measured uranium enrichment, as calculated by the FRAM software, at all positions. However, three cylinders appeared to have local inhomogeneity based on the observed results. This was manifested as very low apparent enrichments, often <10% of the declared enrichment, on select positions. The side with a low apparent enrichment shows elevated daughter isotope activity (e.g., elevated 1001 keV and 766 keV peak count rate) and slightly reduced 235 U activity (lower 185.7 keV count rate). We hypothesize that these heterogenous cylinders may have experienced asymmetric solar heating, which caused volatile UF 6 to sublime preferentially away from the warmed side. A similar phenomenon was observed at a second facility where dose rate measurements confirm that the “low-enriched side” of cylinders show elevated gamma ray dose rates, likely from the removal of UF 6 attenuation and concentration of daughter-products. Care should be taken during uranium enrichment verification when applying methods that include gamma-rays associated with daughter nuclides to the determination of uranium enrichment on cylinders that are stored in sunlight and have asymmetric dose readings around the cylinder.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Porting CMS Heterogeneous Pixel Reconstruction to Kokkos

Programming for a diverse set of compute accelerators in addition to the CPU is a challenge. Maintaining separate source code for each architecture would require lots of effort, and development of new algorithms would be daunting if it had to be repeated many times. Fortunately there are several portability technologies on the market such as Alpaka, Kokkos, and SYCL. These technologies aim to improve the developer productivity by making it possible to use the same source code for many different architectures. In this paper we use heterogeneous pixel reconstruction code from the CMS experiment at the CERNL LHC as a realistic use case of a GPU-targeting HEP reconstruction software, and report experience from prototyping a portable version of it using Kokkos. The development was done in a standalone program that attempts to model many of the complexities of a HEP data processing framework such as CMSSW. We also compare the achieved event processing throughput to the original CUDA code and a CPU version of it.

Childers, Taylor↗

Athena: High-Performance Sparse Tensor Contraction Sequence on Heterogeneous Memory

Sparse tensor contraction sequence has been widely employed in many fields, such as chemistry and physics. However, how to efficiently implement the sequence faces multiple challenges, such as redundant computations and memory operations, massive memory consumption, and inefficient utilization of hardware. To address the above challenges, we introduce Athena, a high-performance framework for SpTC sequences. Athena introduces new data structures, leverages emerging Optane-based heterogeneous memory (HM) architecture, and stage parallelism. In particular, Athena introduces shared hash table-represented sparse accumulator to eliminate unnecessary input processing and data migration; Athena uses a novel data-semantic guided dynamic migration solution to make the best use of the Optane-based HM for high performance; Athena also co-runs execution phases with different characteristics to enable high hardware utilization. Evaluating with 12 datasets, we show that Athena brings 327-7362× speedup over the state-of-the-art SpTC algorithm. With the dynamic data placement guided by data semantics, Athena brings performance improvement on Optane-based HM over a state-of-the-art software-based data management solution, a hardware-based data management solution, and PMM-only by 1.58×, 1.82×, and 2.34× respectively.

Liu, Jiawen↗

Performance Potential of Mixed Data Management Modes for Heterogeneous Memory Systems

Many high-performance systems now include different types of memory devices within the same compute platform to meet strict performance and cost constraints. Such heterogeneous memory systems often include an upper-level tier with better performance, but limited capacity, and lower-level tiers with higher capacity, but less bandwidth and longer latencies for reads and writes. To utilize the different memory layers efficiently, current systems rely on hardware-directed, memory -side caching or they provide facilities in the operating system (OS) that allow applications to make their own data-tier assignments. Since these data management options each come with their own set of trade-offs, many systems also include mixed data management configurations that allow applications to employ hardware- and software-directed management simultaneously, but for different portions of their address space. Despite the opportunity to address limitations of stand-alone data management options, such mixed management modes are under-utilized in practice, and have not been evaluated in prior studies of complex memory hardware. In this work, we develop custom program profiling, configurations, and policies to study the potential of mixed data management modes to outperform hardware- or software-based management schemes alone. Our experiments, conducted on an Intel ® Knights Landing platform with high-bandwidth memory, demonstrate that the mixed data management mode achieves the same or better performance than the best stand-alone option for five memory intensive benchmark applications (run separately and in isolation), resulting in an average speedup compared to the best stand-alone policy of over 10 %, on average.

Effler, Chad↗

Portable Programming Model Exploration for LArTPC Simulation in a Heterogeneous Computing Environment: OpenMP vs. SYCL

The evolution of the computing landscape has resulted in the proliferation of diverse hardware architectures, with different flavors of GPUs and other compute accelerators becoming more widely available. To facilitate the efficient use of these architectures in a heterogeneous computing environment, several programming models are available to enable portability and performance across different computing systems, such as Kokkos, SYCL, OpenMP and others. As part of the High Energy Physics Center for Computational Excellence (HEP-CCE) project, we investigate if and how these different programming models may be suitable for experimental HEP workflows through a few representative use cases. One of such use cases is the Liquid Argon Time Projection Chamber (LArTPC) simulation which is essential for LArTPC detector design, validation and data analysis. Following up on our previous investigations of using Kokkos to port LArTPC simulation in the Wire-Cell Toolkit (WCT) to GPUs, we have explored OpenMP and SYCL as potential portable programming models for WCT, with the goal to make diverse computing resources accessible to the LArTPC simulations. In this work, we describe how we utilize relevant features of OpenMP and SYCL for the LArTPC simulation module in WCT. We also show performance benchmark results on multi-core CPUs, NVIDIA and AMD GPUs for both the OpenMP and the SYCL implementations. Comparisons with different compilers will also be given where appropriate.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Runtime extension for neural network training with heterogeneous memory

Systems, apparatuses, and methods for managing buffers in a neural network implementation with heterogeneous memory are disclosed. A system includes a neural network coupled to a first memory and a second memory. The first memory is a relatively low-capacity, high-bandwidth memory while the second memory is a relatively high-capacity, low-bandwidth memory. During a forward propagation pass of the neural network, a run-time manager monitors the usage of the buffers for the various layers of the neural network. During a backward propagation pass of the neural network, the run-time manager determines how to move the buffers between the first and second memories based on the monitored buffer usage during the forward propagation pass. As a result, the run-time manager is able to reduce memory access latency for the layers of the neural network during the backward propagation pass.

Mappouras, Georgios↗

Federated Machine Learning-Based Anomaly Detection System for Synchrophasor Network Using Heterogeneous Data Sets: Preprint

Synchrophasor technology is widely deployed in the energy management system to monitor the grid health at micro level and perform necessary corrective actions in real time; however, integrated phasor devices and data aggregators are exposed to several cybersecurity threats. This paper proposes a federated ML(FML)-based ADS to detect several data integrity attacks in the synchrophasor network. The proposed approach integrates the horizontal FML technique and consists of substation-based local models and a control center-based global model. The proposed methodology includes training local models using heterogeneous data sets that include network and grid information and updating the global model through multiple iterations by sharing model gradients. Finally, the trained global model is applied to identify cyberattacks, normal operation, and physical events. To validate the proof of concept, we used synthetic data sets generated by Mississippi State University and Oak Ridge National Laboratory for training and testing the classification models using the National Renewable Energy Laboratory's high performance computing resources. Our experimental results, computed through several performance measures, reveal that the proposed approach shows consistent performance during the binary, three-class, and multiclass classifications while ensuring privacy of synchrophasor data.

anomaly detection system↗

Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)

The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environments and operational constraints. Harnessing this data for scientific discovery demands real-time inference and decision-making, intelligent data reduction, and efficient processing architectures beyond current capabilities. Crucial to the success of this experimental paradigm are several emerging technologies, such as artificial intelligence and machine learning (AI/ML) and silicon microelectronics, and the advent of quantum algorithms and processing. Their intersection includes areas of research such as low-power and low-latency devices for edge computing, heterogeneous accelerator systems, reconfigurable hardware, novel codesign and synthesis strategies, readout for cryogenic or high-radiation environments, and analog computing. This white paper presents a community-driven vision to identify and prioritize research and development opportunities in hardware-based ML systems and corresponding physics applications, contributing towards a successful transition to the new data frontier of fundamental science.

Gonski, Julia [SLAC]↗

ECAR-6415 Rev 0 CFD Analysis of the Primary Coolant Apparatus Test Core with Wire Spacers for Heterogeneous Power Distributions

Primary Coolant Apparatus Test (PCAT) is a thermal-hydraulic test loop for Microreactor Applications Research Validation and Evaluation (MARVEL) reactor. The heater elements were manufactured within a straightness tolerance for the designated gap thickness of 1.0 mm, but several elements have been distorted out of tolerance during the welding process. The distortion of heater rods can lead to flow maldistribution and excessive hotspot where the gap between two heater rods is too tight. In order to secure the heater-to-heater gap in an acceptable range, wire spacers are adopted for the PCAT. The wire spacers affect the thermal-hydraulic performance of the PCAT because they enhance the flow mixing among the flow subchannels in the core region. The objectives of this ECAR is to evaluate the effects of the wire spacers on the thermal-hydraulic performance of the PCAT core region by assuming several heterogeneous power distributions.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

A Heterogeneous Palladium Catalyst for the Polymerization of Olefins Prepared by Halide Abstraction Using Surface R 3 Si + Species

The silylium-like surface species [ i Pr 3 Si][(R F O) 3 Al-OSi≡)] activates (N^N)Pd(CH 3 )Cl (N^N=Ar-N=CMeMeC=N-Ar, Ar=2,6-bis(diphenylmethyl)-4-methylbenzene) by chloride ion abstraction to form [(N^N)Pd-CH 3 ][(R F O) 3 Al-OSi≡)] ( 1 ). A combination of FTIR, solid-state NMR spectroscopy, and reactions with CO or vinyl chloride establish that 1 shows similar reactivity patterns as (N^N)Pd(CH 3 )Cl activated with Na[B(Ar F ) 4 ]. Multinuclear 13 C{ 27 Al} RESPDOR and 1 H{ 19 F} S-REDOR experiments are consistent with a weakly coordinated ion-pair between (N^N)Pd-CH 3 + and [(R F O) 3 Al-OSi≡)]. 1 catalyzes the polymerization of ethylene with similar activities as [(N^N)Pd-CH 3 ] + in solution and incorporates up to 0.4% methyl acrylate in copolymerization reactions. 1 produces polymers with significantly higher molecular weight than the solution catalyst, and generates the highest molecular weight polymers currently reported in copolymerization reactions of ethylene and methylacrylate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aldehyde and Ketone Hydroboration Mediated by a Heterogeneous Single–Site Molybdenum–Dioxo Catalyst: Scope and Mechanistic Implications

Efficient hydroboration of aldehydes and ketones is demonstrated using a single-site MoO 2 catalyst supported on activated carbon. Under mild conditions with low catalytic loadings, the reaction exhibits chemoselectivity towards carbonyl reduction over halides, alkene, alkyne, nitrile, and ester groups, affording high yields of desired products. Furthermore, competition studies between aldehyde and ketone reduction using HBpin and HBcat indicate that HBpin preferably functionalizes aldehydes, while HBcat can functionalize either substrate under specific conditions. Mechanistic studies suggest that the reaction proceeds via the initial formation of a molybdenum-hydride species upon B–H activation and subsequent molybdenum-alkoxide species upon carbonyl activation by the Mo center. The experimental activation energy of 14.3 kcal/mol alignssatisfactorily with the DFT computed ΔH ≠ of 18.7 kcal/mol, further supporting the proposed mechanism. Combined experimental/computational analyses reveal that excess HBpin can possibly deactivate the catalyst. The presence of excess benzaldehyde efficiently mitigates deactivation by HBpin, providing significantly higher catalyst recyclability. Altogether, this non-toxic, air- and moisture-stable, active, and selective catalyst demonstrates significant potential for green processes.

08 HYDROGEN↗