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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Substituents effects on the electrocatalytic CO 2 reduction by cobalt corroles in solution

Electrochemical CO 2 reduction catalysis with cobalt corrole complexes in solution is reported. Corroles have attracted attention as contracted and trianionic tetrapyrrolic macrocycles that can be compared to leading porphyrin catalysts for CO 2 reduction, but most studies focus on heterogenized systems with poorly defined electrochemical responses. Electrochemical studies of cobalt corroles bearing axial triphenylphosphine ligands to ensure solubility are reported. The voltammetry provides mechanistic insights supporting CO 2 activation after the formal Co II /Co I reduction. The series of cobalt complexes, including a newly designed corrole with mixed perfluorophenyl/ortho-dimethoxyphenyl substituent pattern, provide evidence for electron-rich catalysts having stronger interactions with CO 2 . The primary product of CO 2 reduction is CO, formed at a rate of ca. 90 s −1 .

Kumar, Sachin [Technion–Israel Institute of Techno↗
DOE OSTI2015

Distributed feedback terahertz frequency quantum cascade lasers with dual periodicity gratings

We have developed terahertz frequency quantum cascade lasers that exploit a double-periodicity distributed feedback grating to control the emission frequency and the output beam direction independently. The spatial refractive index modulation of the gratings necessary to provide optical feedback at a fixed frequency, and simultaneously, a far-field emission pattern centered at controlled angles, was designed through use of an appropriate wavevector scattering model. Single mode terahertz (THz) emission at angles tuned by design between 0° and 50° was realized, leading to an original phase-matching approach for highly collimated THz quantum cascade lasers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Improved filters for angular filter refractometry

Angular filter refractometry is an optical diagnostic that measures the absolute contours of a line-integrated density gradient by placing a filter with alternating opaque and transparent zones in the focal plane of a probe beam, which produce corresponding alternating light and dark regions in the image plane. Identifying transitions between these regions with specific zones on the angular filter (AF) allows the line-integrated density to be determined, but the sign of the density gradient at each transition is degenerate and must be broken using other information about the object plasma. Additional features from diffraction in the filter plane often complicate data analysis. Here, in this paper, we present an improved AF design that uses a stochastic pixel pattern with a sinusoidal radial profile to minimize unwanted diffraction effects in the image caused by the sharp edges of the filter bands. We also present a technique in which a pair of AFs with different patterns on two branches of the same probe beam can be used to break the density gradient degeneracy. Both techniques are demonstrated using a synthetic diagnostic and data collected on the OMEGA EP (extended performance) laser.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Predicting Lung Cancer Incidence from Air Pollution Exposures Using Shapelet-based Time Series Analysis

In this paper we investigated whether the geographical variation of lung cancer incidence can be predicted through examining the spatiotemporal trend of particulate matter air pollution levels. Regional trends of air pollution levels were analyzed by a novel shapelet-based time series analysis technique. First, we identified U.S. counties with reportedly high and low lung cancer incidence between 2008 and 2012 via the State Cancer Profiles provided by the National Cancer Institute. Then, we collected particulate matter exposure levels (PM2.5 and PM10) of the counties for the previous decade (1998-2007) via the AirData dataset provided by the Environmental Protection Agency. Using shapelet-based time series pattern mining, regional environmental exposure profiles were examined to identify frequently occurring sequential exposure patterns. Finally, a binary classifier was designed to predict whether a U.S. region is expected to experience high lung cancer incidence based on the region’s PM2.5 and PM10 exposure the decade prior. The study confirmed the association between prolonged PM exposure and lung cancer risk. In addition, the study findings suggest that not only cumulative exposure levels but also the temporal variability of PM exposure influence lung cancer risk.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

MICCO: An Enhanced Multi-GPU Scheduling Framework for Many-Body Correlation Functions

Calculation of many-body correlation functions is one of the critical kernels utilized in many scientific computing areas, especially in Lattice Quantum Chromodynamics (Lattice QCD). It is formalized as a sum of a large number of contraction terms each of which can be represented by a graph consisting of vertices describing quarks inside a hadron node and edges designating quark propagations at specific time intervals. Due to its computation- and memory-intensive nature, real-world physics systems (e.g., multi-meson or multi-baryon systems) explored by Lattice QCD prefer to leverage multi-GPUs. Different from general graph processing, many-body correlation function calculations show two specific features: a large number of computation-/data-intensive kernels and frequently repeated appearances of original and intermediate data. The former results in expensive memory operations such as tensor movements and evictions. The latter offers data reuse opportunities to mitigate the data-intensive nature of many-body correlation function calculations. However, existing graph-based multi-GPU schedulers cannot capture these data-centric features, thus resulting in a sub-optimal performance for many-body correlation function calculations. To address this issue, this paper presents a multi-GPU scheduling framework, MICCO, to accelerate contractions for correlation functions particularly by taking the data dimension (e.g., data reuse and data eviction) into account. This work first performs a comprehensive study on the interplay of data reuse and load balance, and designs two new concepts: local reuse pattern and reuse bound to study the opportunity of achieving the optimal trade-off between them. Based on this study, MICCO proposes a heuristic scheduling algorithm and a machine-learning-based regression model to generate the optimal setting of reuse bounds. Specifically, MICCO is integrated into a real-world Lattice QCD system, Redstar, for the first time running on multiple GPUs. The evaluation demonstrates MICCO outperforms other state-of-art works, achieving up to 2.25× speedup in synthesized datasets, and 1.49× speedup in real-world correlation functions.

Wang, Qihan↗
DOE OSTI2020

Binary pseudorandom array test standard optimized for characterization of large field-of-view optical interferometers

Recently, a technique for calibrating the modulation transfer function (MTF) of a broad variety of metrology instrumentation has been demonstrated. This technique is based on test samples structured as one-dimensional binary pseudo-random (BPR) sequences and two-dimensional BPR arrays (BPRAs). The inherent power spectral density of BPR gratings (sequences) and arrays has a deterministic white-noise-like character that allows direct determination of the MTF with uniform sensitivity over the entire spatial frequency range and field-of-view of an instrument. As such, the BPR samples satisfy the characteristics of a test standard: functionality, ease of specification and fabrication, reproducibility, and low sensitivity to manufacturing error. Here we discuss our recent developments directed to the optimization of the sample design, fabrication, application, and data processing procedures, suitable for thorough characterization of large aperture optical interferometers. Compared with the previous coded-aperture based design, the improved, 'highly randomized' BPRA pattern of the new test standard provides better accuracy and reliability of instrument MTF and aberration characterization, and enables operation optimization of large aperture optical interferometers. We describe the pattern generation algorithm and tests to verify the compliance to desired BPRA topography. The data acquisition and analysis procedures for different applications of the technique are also discussed.

Yashchuk, Valeriy V.↗
DOE OSTI2021

Plateau Phenomenon in Gradient Descent Training of RELU Networks: Explanation, Quantification, and Avoidance

The ability of neural networks to provide ‘best in class’ approximation across a wide range of applications is well-documented. Nevertheless, the powerful expressivity of neural networks comes to naught if one is unable to effectively train (choose) the parameters defining the network. In general, neural networks are trained by gradient descent type optimization methods,a stochastic variant thereof. In practice, such methods result in the loss function decreases rapidly at the beginning of training but then, after a relatively small number of steps, significantly slow down. The loss may even appear to stagnate over the period of a large number of epochs, only to then suddenly start to decrease fast again for no apparent reason. This so-called plateau phenomenon manifests itself in many learning tasks. The present work aims to identify and quantify the root causes of plateau phenomenon.analysis is carried out in the setting of univariate ReLU networks. No assumptions are made on the number of neurons relative to the number of training data, and our results hold for both the lazy and adaptive regimes. Here, the main findings are: plateaux correspond to periods during which activation patterns remain constant, where activation pattern refers to the number of data points that activate a given neuron; quantification of convergence of the gradient flow dynamics; and, characterization stationary points in terms solutions of local least squares regression lines over subsets of the training data. Based on these conclusions, we propose a new iterative training method, the Active Neuron Least Squares (ANLS), characterised by the explicit adjustment of the activation pattern at each step, which is designed to enable a quick exit from a plateau. Illustrative numerical examples are included throughout.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

All Source Sensor Analysis

ASSA is a software application that processes binary data into summarized index tables that can be used to organize features contained within the data. ASSA's index tables can also be used to search for user specified features. ASSA is designed to organize and search for patterns in unstructured binary data streams or archives, such as video, images, audio, and network traffic. ASSA is basically a very general search engine used to search for any pattern in any binary data stream. It has uses in video analytics, image analysis, audio analysis, searching hard-drives, monitoring network traffic, etc.

Trease, Harold↗
DOE OSTI2012

Global Access-controlled Transfer e-frame (GATe)

Global Access-controlled Transfer e-frame (GATe) was designed to take advantage of the patterns that occur during an electronic record transfer process. The e-frame (or electronic framework or platform) is the foundation for developing secure information transfer to meet classified and unclassified business processes and is particularly useful when there is a need to share information with various entities in a controlled and secure environment. It can share, search, upload, download and retrieve sensitive information, as well as provides reporting capabilities.

Forsmann, Hope↗
DOE OSTI2024

Dry etching of epitaxial InGaAs/InAlAs/InAlGaAs structures for fabrication of photonic integrated circuits

A dry etching process to transfer the pattern of a photonic integrated circuit design for high-speed laser communications is described. The laser stack under consideration is a 3.2-µm-thick InGaAs/InAlAs/InAlGaAs epitaxial structure grown by molecular beam epitaxy. The etching was performed using Cl2-based inductively-coupled-plasma and reactive-ion-etching (ICP-RIE) reactors. Four different recipes are presented in two similar ICP-RIE reactors, with special attention paid to the etched features formed with various hard mask compositions, in-situ passivations, and process temperatures. The results indicate that it is possible to produce high-aspect-ratio features with sub-micron separation on this multilayer structure. Additionally, the results of the etching highlight the tradeoffs involved with the corresponding recipes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

FY13 Annual Report:APEEM Components Analysis and Evaluation

The objectives of this evaluation is to Support the evaluation of current and proposed electric machine and power electronics technologies in a vehicle context to understand the applicability of a particular powertrain technology to a given vehicle and to determine areas/regions for component design improvement based upon system usage patterns; and Enhance the current benchmarking and prototype evaluation capabilities of DOE APEEM programs with the addition of transient-capable testing facilities for power electronics and electric machinery components.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

An Assessment of Envelope Measures in Mild Climate Deep Energy Retrofits

Energy end-uses and interior comfort conditions have been monitored in 11 Deep Energy Retrofits (DERs) in a mild marine climate. Two broad categories of DER envelope were identified: first, bringing homes up to current code levels of insulation and airtightness, and second, enhanced retrofits that go beyond these code requirements. The efficacy of envelope measures in DERs was difficult to determine, due to the intermingled effects of enclosure improvements, HVAC system upgrades and changes in interior comfort conditions. While energy reductions in these project homes could not be assigned to specific improvements, the combined effects of changes in enclosure, HVAC system and comfort led to average heating energy reductions of 76percent (12,937 kWh) in the five DERs with pre-retrofit data, or 80percent (5.9 kWh/ft2) when normalized by floor area. Overall, net-site energy reductions averaged 58percent (15,966 kWh; n=5), and DERs with code-style envelopes achieved average net-site energy reductions of 65percent (18,923 kWh; n=4). In some homes, the heating energy reductions were actually larger than the whole house reductions that were achieved, which suggests that substantial additional energy uses were added to the home during the retrofit that offset some heating savings. Heating system operation and energy use was shown to vary inconsistently with outdoor conditions, suggesting that most DERs were not thermostatically controlled and that occupants were engaged in managing the indoor environmental conditions. Indoor temperatures maintained in these DERs were highly variable, and no project home consistently provided conditions within the ASHRAE Standard 55-2010 heating season comfort zone. Thermal comfort and heating system operation had a large impact on performance and were found to depend upon the occupant activities, so DERs should be designed with the occupants needs and patterns of consumption in mind. Beyond-code building envelopes were not found to be strictly necessary for the achievement of deep energy savings in existing uninsulated homes in mild marine climates, provided that other energy end-uses were comprehensively reduced. We recommend that mild climate DERs pursue envelopes in compliance with the 2012 International Energy Conservation Code (IECC) and pair these with high efficiency, off-the-shelf HVAC equipment. Enhanced building envelopes should be considered in cases where very low heating energy use (<1,000 kWh/year or <0.5 kWh/ft2-year) and enhanced thermal comfort (ASHRAE 55-2010) are required, as well as in those situations where substantial energy uses are added to the home, such as decorative lighting, cooling or smart home A/V and communication equipment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

New Strategies for 0.5 mm Resolution, High Sensitivity, Multi- Radionuclide Imaging

This project constitutes a 0.5-millimeter resolution radionuclide detector system built from CZT. (1) A novel dual-crystal photon detector module design with cross-strip electrode patterns was developed; (2) The module mechanical assembly was built; (3) A data acquisition (DAQ) chain for the module was produced; (4) A software tool was developed to incorporate novel time and energy measurement calibration techniques. (5) A small multi-detector prototype of the radionuclide imaging system was built from this module for system-level characterizations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

DITAC FASPAX / ASIC Development [Slides]

FASPAX is an integrating detector with wide dynamic range and high burst frame rate. The detector uses in-pixel analog storage to acquire a burst of images at frame rates of up to 13 MHz, with further provision for user-defined timing schemes. The detector allows the synchrotron light source time-resolved community to access the machine's designed temporal resolution for particular fill patterns.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Large-Scale Reactive Extrusion Deposition of Sparse Infill Structures with Solid Perimeters

Large-scale additive manufacturing of reactive polymer systems offers significant improvements over thermoplastics through improved mechanical properties, faster deposition rates, and deposition at ambient temperatures. At ambient temperatures, the resin exists as a viscoelastic liquid which require additional additives for improved rigidity and bead stability. These filler-reinforced resins, or yield stress fluids, are soft solid-like materials able to withstand compressive forces from successive layer deposition until curing leads to bead solidification. When bead deposition is unsupported by previous layers, as is the case when bridging a gap, the creep due to gravitational loading can lead to bead instabilities which result in excessive sagging or bead breakage. These bead instabilities are material dependent and susceptible to changes in filler composition and temperature rises due to exothermic reactions. This work implements a design solution for bridging sparse infill patterns in additively manufactured parts which are essential in the reduction of weight. A series of span tests over a range of distances, as multiples of nozzle diameter, were conducted to determine the critical distance where a bead would break. Additional layer depositions determined the number of layers needed to recover from sagging effects. This recovery was essential in the transition of sparse infill to solid infill printing, where solid infill is milled for a smooth surface finish. Without the capability of sparse-solid transition, additively manufactured parts would require further surface treatments such as spray coating, adding to cost and increasing production time. A standard domed-mold geometry is presented to show the success of this printing process.

Hershey, Christopher↗
DOE OSTI2020

RL-HEMS: Reinforcement Learning Based Home Energy Management System for HVAC Energy Optimization

Heating, ventilation, and air conditioning (HVAC) is one of the major energy consumers in the residential sector. It is important to be able to monitor and control the energy consumed to provide utility services such as load shaping while satisfying the comfort and economic constraints of the homeowner. The objective of this work is to create the optimal schedule for HVAC operation to reduce the cost while satisfying the home-owner and equipment’s constraints using a model-free Reinforcement Learning (RL)-based optimization. The specific goal is to find the right balance between reducing energy cost, consumption, and customer comfort level. Our research effort addresses this optimization problem using multiple components: the development of initial learning test-bed and implementation of RL techniques on a real home. This will enable the rapid evaluation of the RL techniques and provide an early baseline to train before implementation on site. The RL algorithm is designed to learn the energy use patterns and generate the optimized schedule for HVAC within an acceptable time-interval to satisfy the homeowner’s comfort and minimize the energy usage. Our preliminary results are promising and we have observed a 17% reduction in the total cost and a 15% reduction in the power utilization using our RL-based HVAC model—RL-HEMS.

Kotevska, Olivera↗