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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

An overview of process systems engineering approaches for process intensification: State of the art

Process intensification offers the potential to drastically reduce the energy consumption and cost of producing chemicals from both bulk and distributed feedstocks. This review article aims to offer an extensive survey on state-of-the-art process systems engineering (PSE) approaches for process intensification. From both academic and industrial perspectives, this paper provides an overview of the development of various process intensification technologies, specifically those under the categories of separation, reaction, hybrid reaction/separation, and alternative energy sources. A current status analysis in the areas of modeling and simulation is then provided. An indicative list of PSE publications specialized on process intensification is presented to illustrate the progresses made so far towards the deployment of novel process intensification technologies. We also highlight some recent advances for the modeling, design, and synthesis of intensified systems, as well as for the assessment of their controllability/operability/safety performance. As a result, key open questions in these areas include: (i) how to systematically derive intensified designs, and (ii) how to ensure the operability and optimality of the derived intensified structures while delivering their expected functionality.

42 ENGINEERING↗
DOE OSTI2017

Low-dose-rate Brachytherapy for Prostate Cancer in Low-resource Settings

Purpose: In areas with limited health care, it is important to identify and implement effective treatment methods and to optimize available resources. We investigated the implementation of a low-dose-rate (LDR) brachytherapy program for the treatment of prostate cancer (PCa) in a low-resource setting such as Puerto Rico (PR), where PCa is the main cause of cancer-associated death. Methods and Materials: After institutional approval, the medical records of patients with nonmetastatic PCa undergoing LDR brachytherapy from 2008 to 2013 were reviewed from PR. The factors analyzed included adequate D{sub 90} (radiation dose delivered to 90% of the target volume) coverage (≥140 Gy), early and late toxicity (Common Terminology Criteria for Adverse Events grade >2), and prostate-specific antigen failure. Freedom from biochemical failure was evaluated using Kaplan-Meier analysis. Results: The barriers to implementation of LDR brachytherapy in a country with limited resources were identified. These included lack of access to funding for startup costs, specific referral patterns, lack of trained support staff, such as dosimetrists and physicists, and initial opposition from insurance companies for reimbursement. The initial results from 191 patients were included in the present study with a median follow-up period of 26 months. Prostate-specific antigen failure occurred in 6 patients (3%). No early or late gastrointestinal toxicity (grade >2) developed. Only 3 (2%) and 2 (1%) patients experienced early and late genitourinary toxicity (grade >2), respectively. The 2- and 3-year freedom from biochemical failure in this population was 97% and 95.9%, respectively. Conclusions: At present, limited data are available delineating the barriers faced by low-resource settings in the implementation of LDR brachytherapy. Our data highlight the issues unique to this environment and support the use of LDR brachytherapy as a reliable and effective treatment modality for patients with PCa in low-resource settings.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

A remote sensing method for estimating regional reservoir area and evaporative loss

Evaporation from the water surface of a reservoir can significantly affect its function of ensuring the availability and temporal stability of water supply. Current estimations of reservoir evaporative loss are dependent on water area derived from a reservoir storage-area curve. Such curves are unavailable if the reservoir is located in a data-sparse region or questionable if long-term sedimentation has changed the original elevation-area relationship. In this paper, we propose a remote sensing framework to estimate reservoir evaporative loss at the regional scale. This framework uses a multispectral water index to extract reservoir area from Landsat imagery and estimate monthly evaporation volume based on pan-derived evaporative rates. The optimal index threshold is determined based on local observations and extended to unobserved locations and periods. Built on the cloud computing capacity of the Google Earth Engine, this framework can efficiently analyze satellite images at large spatiotemporal scales, where such analysis is infeasible with a single computer. Our study involves 200 major reservoirs in Texas, captured in 17,811 Landsat images over a 32-year period. The results show that these reservoirs contribute to an annual evaporative loss of 8.0 billion cubic meters, equivalent to 20% of their total active storage or 53% of total annual water use in Texas. At five coastal basins, reservoir evaporative losses exceed the minimum freshwater inflows required to sustain ecosystem health and fishery productivity of the receiving estuaries. Reservoir evaporative loss can be significant enough to counterbalance the positive effects of impounding water and to offset the contribution of water conservation and reuse practices. Our results also reveal the spatially variable performance of the multispectral water index and indicate the limitation of using scene-level cloud cover to screen satellite images. Finally, this study demonstrates the advantage of combining satellite remote sensing and cloud computing to support regional water resources assessment.

58 GEOSCIENCES↗
DOE OSTI2019

Surpassing the 10% efficiency milestone for 1-cm 2 all-polymer solar cells

Naphthalenediimide-based n-type polymeric semiconductors are extensively used for constructing high-performance all-polymer solar cells (all-PSCs). For such all-polymer systems, charge recombination can be reduced by using thinner active layers, yet suffering insufficient near-infrared light harvesting from the polymeric acceptor. Conversely, increasing the layer thickness overcomes the light harvesting issue, but at the cost of severe charge recombination effects. Here we demonstrate that to manage light propagation within all-PSCs, a thick bulk-heterojunction film of approximately 350 nm is needed to effectively enhance photo-harvesting in the near-infrared region. To overcome the severe charge recombination in such a thick film, a non-halogenic additive is used to induce a well-ordered micro-structure that inherently suppresses recombination loss. The combined strategies of light management and delicate morphology optimization lead to a promising efficiency over 10% for thick-film all-PSCs with active area of 1 cm 2 , showing great promise for future large-scale production and application of all-PSCs.

14 SOLAR ENERGY↗
DOE OSTI2018

Influence of graphene thickness and grain boundaries on MoS 2 wrinkle nanostructures

Controlling wrinkle nanostructures of two-dimensional materials is critical for optimizing the material properties and device performance. Herein, we demonstrated the in situ synthesis of large-area MoS 2 wrinkles on graphene by chemical-vapor-deposition-assisted sulfurization, and investigated the influence of graphene thickness and grain structures on the feature dimensions of MoS 2 wrinkle nanostructures. The height, width, and overall surface roughness of the MoS 2 wrinkles diminish as the number of graphene layers increases, which was further verified by determining the binding energy of graphene layers by density functional theory calculations. Furthermore, the feature dimensions of MoS 2 wrinkle nanostructures were also influenced by graphene domain boundaries because of the difference in graphene nucleation density. This may be attributed to the influence of the mechanical properties of graphene substrates on the overall feature dimensions of MoS 2 wrinkles, which are directly correlated with the interfacial adhesion energy. We believe that our findings may contribute toward the controllable synthesis of MoS 2 wrinkle nanostructures and other two-dimensional materials used for high-performance devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

O’Hare Airport Short-Term Ground Transportation Modal Demand Forecast Using Gaussian Processes

Here, the principal objective of this study is to analyze the spatial and temporal variation of ground transportation airport demand and provide demand forecast to inform planning capability and explore alternatives for investments to accommodate airport growth. Because of its good adaptability and strong generalization ability for dealing with high-dimensional input, small-sample, and nonlinear spatial data, Gaussian process (GP) regression is used to provide forecast estimates using data from transportation network company (TNC) trips and urban rail passengers at Chicago's O'Hare International Airport. TNC airport trips differ significantly, with three times more distance, more than twice the travel time, and half of the share requests compared with nonairport trips. This highlights the need for separate demand models. Hourly analysis of the rail service indicates that this is likely heavily used by airport workers, whereas TNC services focus on travelers because of variations in the peak demand hours. Heteroscedastic GP regression is implemented because of differences in trip variance between night and day hours. Estimates are given for weekdays and weekend trips, and the 95% confidence intervals are calculated. The introduction of flight schedule information into the models shows marginal improvements in their performance. However, fitting a GP regression becomes computationally expensive with increased sample size and the introduction of spatial components. Transportation planners and policymakers can use the results and methods implemented in this study to optimize transportation assets and provide long-range simulations of the current and future conditions in the area.

42 ENGINEERING↗
DOE OSTI2022

Throughput-Oriented and Accuracy-Aware DNN Training with BFloat16 on GPU

Deep Neural Networks (DNNs) have transformed the field of artificial intelligence and achieved extraordinary success in many areas. The training of DNNs is commonly compute and memory-intensive, which has resulted in several optimizations in the training phase. Among them, reduced precision is a typical and widely used technique to accelerate DNN training and reduce memory requirements. However, applying a widely adopted reduced precision format such as Float16 to all involved operations in DNN training is not optimal as the use of Float16 in some operations can hurt model accuracy. Meanwhile, additional optimizations including loss scaling and autocast techniques can mitigate the accuracy loss but lead to inherent overhead and inadequate use of reduced precision. In this work, we leverage another reduced precision format, BFloat16, and introduce a throughput-oriented and accuracy-aware approach to maximize the performance potential of DNN training. Since the high throughput provided by BFloat16 format is accompanied by low precision of the floating-point representation, this approach achieves high throughput by using BFloat16 on all DNN operations and avoids the accuracy loss through a customized accuracy-aware normalization. Results show that our approach outperforms the state-of-the-art mixed-precision training by 1.21x on an NVIDIA A100 GPU.

Xie, Zhen↗
DOE OSTI2024

Object Proxy Patterns for Accelerating Distributed Applications

Workflow and serverless frameworks have empowered new approaches to distributed application design by abstracting compute resources. However, their typically limited or one-size-fits-all support for advanced data flow patterns leaves optimization to the application programmer—optimization that becomes more difficult as data become larger. The transparent object proxy, which provides wide-area references that can resolve to data regardless of location, has been demonstrated as an effective low-level building block in such situations. Here we propose three high-level proxy-based programming patterns—distributed futures, streaming, and ownership—that make the power of the proxy pattern usable for more complex and dynamic distributed program structures. We motivate these patterns via careful review of application requirements and describe implementations of each pattern. As a result, we evaluate our implementations through a suite of benchmarks and by applying them in three meaningful scientific applications, in which we demonstrate substantial improvements in runtime, throughput, and memory usage.

Distributed Computing↗
DOE OSTI2023

Smart Preprocessing & Robust Integration Emulator

To achieve the desired particle size of biomass feedstocks during preprocessing for trouble-free handling and conversion to produce biofuels and bioproducts, the raw materials must undergo a crucial milling process. The particle size of biomass plays a critical role in subsequent biofuel manufacturing, where a larger area-to-volume ratio facilitates efficient synthesis while balancing the impact of moisture on biomass storage. To optimize biofuel production efficiency and overcome these challenges, it is imperative to accurately predict the particle size distribution (PSD) of the biomass in the design of efficient preprocessing systems. The population balance model (PBM), upon empirical calibration and validation, can provide rapid prediction of post-milling PSD of granular biomass. However, PSD has limitations related to mass conservation and the absence of moisture considerations. To overcome these drawbacks, a deep learning model called the enhanced deep neural operator (DNO+) is implemented in the code. This model not only retains the capabilities of the PBM in handling complex mapping functions but also incorporates additional factors influencing the system. By considering various experimental conditions such as sieve size and moisture content, the trained DNO+ model can effectively predict the PSD after milling for any given feed PSD. To further reduce the reliance on experimental data, the PBM is integrated into the DNO+ model, resulting in a physics-informed DNO+ (PIDNO+). The PIDNO+ model addresses the non-conservation of quality exhibited by the PBM while inheriting the advantages of the DNO+ model in considering multiple influencing factors. Moreover, the PIDNO+ model significantly reduces the amount of data required for model training. Both deep learning models, i.e., DNO+ and PIDNO+, are excellent in predictive performance, offering swift and accurate machine learning-based predictions. The use of this code that contains these models will assist in guiding the proper milling equipment selection and operational conditions to achieve the desired biomass particle sizes, ensuring the efficiency of subsequent biofuel and bioproduct production processes.

Xia, Yidong [Idaho National Laboratory (INL), Idah↗
DOE OSTI2023

An Active and Resilient Bilayer Oxygen Electrode for Intermediate Temperature Reversible Solid Oxide Cells

High temperature solid oxide cells (SOCs) have intrinsic advantage in efficiency over conventional internal combustion engines for power generation and low-temperature electrolysis cells for H2 production. This efficiency advantage could potentially lead to cost saving and emission reduction. However, commercialization of the current SOCs technology is hindered by its poor durability. One major component with the durability issue is oxygen electrode (OE). For example, the durability of OEs can be negatively affected by the gaseous Cr-species originated from the air oxidation of high-temperature alloy interconnect. For electrolysis operation, on the other hand, delamination of OE from electrolyte, particularly at high current densities, has been identified as a major cause for the performance degradation. Therefore, developing robust and active OEs is of critical importance to SOC technology. WE have previously demonstrated a new bilayer OE with strong activity and stability. Here in this presentation, we present recent results of electrochemical characterization on bilayer OE operating under both fuel cell and electrolysis modes. We will first show the optimization of bilayer OE in terms of thickness, morphology, and calcination temperature and their impacts on cell area specific resistance (ASR). With three-electrode symmetric cell configuration, we also show the results of charge transfer ASR of bilayer OE as a function of current density, temperature, and time in different atmospheres. The results are further compared with the baseline OE (LSCF+GDC) to demonstrate the advantage of bilayer OE.

Huang, Kevin↗
DOE OSTI2025

Summary of the 1st Reactor Graphite Workshop, 8-9 July, 2025

Graphite is widely used as moderator in many fission reactors and other criticality systems. The understanding of its short- and long-term behavior in fission environments is crucial not only for the operation and optimization of existing reactors but also for the efficient design and safe deployment of future advanced reactors. It is thus of utmost importance to incorporate in nuclear data libraries accurate evaluations of the interaction of thermal neutrons with graphite used in applications. This is however a complex task as there are challenges in defining the detailed characterizations of the studied material, appropriate modeling, and optimal validation suite. This will only be achieved by the concerted effort of experts of all relevant areas.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

An empirical method for geometric calibration of a photon counting detector-based cone beam CT system

BACKGROUND: Geometric calibration is essential in developing a reliable computed tomography (CT) system. It involves estimating the geometry under which the angular projections are acquired. Geometric calibration of cone beam CTs employing small area detectors, such as currently available photon counting detectors (PCDs), is challenging when using traditional-based methods due to detectors’ limited areas. OBJECTIVE: This study presented an empirical method for the geometric calibration of small area PCD-based cone beam CT systems. METHODS: Unlike the traditional methods, we developed an iterative optimization procedure to determine geometric parameters using the reconstructed images of small metal ball bearings (BBs) embedded in a custom-built phantom. An objective function incorporating the sphericities and symmetries of the embedded BBs was defined to assess performance of the reconstruction algorithm with the given initial estimated set of geometric parameters. The optimal parameter values were those which minimized the objective function. The TIGRE toolbox was employed for fast tomographic reconstruction. To evaluate the proposed method, computer simulations were carried out using various numbers of spheres placed in various locations. Furthermore, efficacy of the method was experimentally assessed using a custom-made benchtop PCD-based cone beam CT. RESULTS: Computer simulations validated the accuracy and reproducibility of the proposed method. The precise estimation of the geometric parameters of the benchtop revealed high-quality imaging in CT reconstruction of a breast phantom. Within the phantom, the cylindrical holes, fibers, and speck groups were imaged in high fidelity. The CNR analysis further revealed the quantitative improvements of the reconstruction performed with the estimated parameters using the proposed method. CONCLUSION: Apart from the computational cost, we concluded that the method was easy to implement and robust.

Instruments & Instrumentation↗
DOE OSTI2020

Multi-Size Proppant Pumping Schedule of Hydraulic Fracturing: Application to a MP-PIC Model of Unconventional Reservoir for Enhanced Gas Production

Slickwater hydraulic fracturing is becoming a prevalent approach to economically recovering shale hydrocarbon. It is very important to understand the proppant’s transport behavior during slickwater hydraulic fracturing treatment for effective creation of a desired propped fracture geometry. The currently available models are either oversimplified or have been performed at limited length scales to avoid high computational requirements. Another limitation is that the currently available hydraulic fracturing simulators are developed using only single-sized proppant particles. Motivated by this, in this work, a computationally efficient, three-dimensional, multiphase particle-in-cell (MP-PIC) model was employed to simulate the multi-size proppant transport in a field-scale geometry using the Eulerian–Lagrangian framework. Instead of tracking each particle, groups of particles (called parcels) are tracked, which allows one to simulate the proppant transport in field-scale geometries at an affordable computational cost. Then, we found from our sensitivity study that pumping schedules significantly affect propped fracture surface area and average fracture conductivity, thereby influencing shale gas production. Motivated by these results, we propose an optimization framework using the MP-PIC model to design the multi-size proppant pumping schedule that maximizes shale gas production from unconventional reservoirs for given fracturing resources.

42 ENGINEERING↗
NASA NTRS1972

Stress Analysis and Design of Silicon Solar Cell Arrays and Related Material Properties

A systematic approach is presented for the design of solar cell arrays to eliminate mechanical failures that might arise in components of the arrays in a thermal environment. A prerequisite to the approach is the characterization of material properties at different temperatures. Significant data is obtained for the thermal behavior of the silicon solar cell material and adhesives. Upon determining the mechanical and thermal material properties of the components of the solar cell array, utilizing a finite element idealization for predicting the stress fields in the components, and employing the von Mises failure criterion, potential failure areas in various design configurations in a given thermal environment are identified. Guide lines and means to optimize a given design are illustrated by two examples.

Salama, A. M.↗
NASA NTRS1973

Application of ERTS-1 data to the protection and management of New Jersey's coastal environment

ERTS-1 imagery is being used by the New Jersey Department of Environmental Protection (NJDEP) to develop information products that will assist the state in optimally managing its coastal resources and in allocating funds. Interviews with NJDEP personnel have identified significant problem areas in the coastal zone, and the types of remote sensor derived information products that can be used in real-time decision making. Initial analyses of imagery from several successive ERTS-1 orbits have shown the extent, predominant drift, and dispersion characteristics of waste disposal in coastal New Jersey waters. Imagery (MSS Bands 4 and 5) for several orbits, shows that New-York Harbor tidal discharge extending as far south as Long Branch, New Jersey.

Mairs, R. L.↗
NASA NTRS1985

Analysis of potential helicopter vibration reduction concepts

Results of analytical investigations to develop, understand, and evaluate potential helicopter vibration reduction concepts are presented in the following areas: identification of the fundamental sources of vibratory loads, blade design for low vibration, application of design optimization techniques, active higher harmonic control, blade appended aeromechanical devices, and the prediction of vibratory airloads. Primary sources of vibration are identified for a selected four-bladed articulated rotor operating in high speed level flight. The application of analytical design procedures and optimization techniques are shown to have the potential for establishing reduced vibration blade designs through variations in blade mass and stiffness distributions, and chordwise center-of-gravity location.

Landgrebe, A. J.↗
NASA NTRS1989

DSN 70-meter antenna microwave optics design and performance improvements. Part 1: Design optimization

The design optimizations associated with the microwave and structural upgrade of the DSN 64-m antennas are discussed. Expected area efficiency/gain performances at S- and X-band are given for both the original 64-m systems and the upgraded 70-m systems, and error estimates are developed. The DSN 70-m Upgrade Project specifications, based on predesign estimates, were 1.4-dB gain at S-band and 1.9-dB at X-band, with no degradation to critical receiving system noise temperatures. The measurements show an S-band gain increase of 1.9 dB and an average increase of 2.1 dB at X-band. The Project also delivered small receiving system noise decreases at both frequency bands. The three DSN 70-m antennas, in the initial state of mechanical adjustment as of the end of calendar year 1988, are performing with very high peak microwave area efficiencies at very nearly the engineering design expectations of 76 percent at S-band and 71 percent at X-band.

Bathker, D. A.↗
NASA NTRS1990

The spatial distribution of p-mode absorption in active regions

The interaction of solar p-mode waves and active regions has been the subject of recent observational and theoretical investigations. Observations show that up to one-half of the power of incident high-degree acoustic may be absorbed in and around sunspots. In this paper the horizontal spatial distribution of high-degree p-mode absorption in solar active regions is explored. An appropriate Fourier-Hankel transform can be used to detect the mean absorption of waves passing through any given point on the solar surface. By repeating the analysis at multiple positions a map of the absorption can be constructed. A technique for optimal computation of absorption maps is developed and applied to observations of several active regions and an area of quiet sun near disk center. By comparing the distribution of p-mode absorption with magnetograms and line-wing intensity images, it is directly observed that the absorption is not limited to the location of the visible sunspots but is also associated with magnetic fields in the surrounding plage. It is estimated that the absorption efficiency scales roughly with the magnetic flux density, although the absorption appears to saturate inside the strongest fields.

Braun, D. C.↗