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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Critical point analysis of phase envelope diagram

Phase diagram or phase envelope is a relation between temperature and pressure that shows the condition of equilibria between the different phases of chemical compounds, mixture of compounds, and solutions. Phase diagram is an important issue in chemical thermodynamics and hydrocarbon reservoir. It is very useful for process simulation, hydrocarbon reactor design, and petroleum engineering studies. It is constructed from the bubble line, dew line, and critical point. Bubble line and dew line are composed of bubble points and dew points, respectively. Bubble point is the first point at which the gas is formed when a liquid is heated. Meanwhile, dew point is the first point where the liquid is formed when the gas is cooled. Critical point is the point where all of the properties of gases and liquids are equal, such as temperature, pressure, amount of substance, and others. Critical point is very useful in fuel processing and dissolution of certain chemicals. Here in this paper, we will show the critical point analytically. Then, it will be compared with numerical calculations of Peng-Robinson equation by using Newton-Raphson method. As case studies, several hydrocarbon mixtures are simulated using by Matlab.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A robust deep learning workflow to predict multiphase flow behavior during geological C O 2 sequestration injection and Post-Injection periods

Simulation of multiphase flow in porous media is essential to manage the geologic CO 2 sequestration (GCS) process, and physics-based simulation approaches usually take prohibitively high computational cost due to the nonlinearity of the coupled physics. This paper contributes to the development and evaluation of a deep learning workflow that accurately and efficiently predicts the temporal-spatial evolution of pressure and CO 2 plumes during injection and post-injection periods of GCS operations. Based on a Fourier Neural Operator, the deep learning workflow takes input variables or features including rock properties, well operational controls and time steps, and predicts the state variables of pressure and CO 2 saturation. To further improve the predictive fidelity, separate deep learning models are trained for CO 2 injection and post-injection periods due to the difference in primary driving force of fluid flow and transport during these two phases. We also explore different combinations of features to predict the state variables. We use a realistic example of CO 2 injection and storage in a 3D heterogeneous saline aquifer, and apply the deep learning workflow that is trained from physics-based simulation data and emulate the physics process. Through this numerical experiment, we demonstrate that using two separate deep learning models to distinguish post-injection from injection period generates the most accurate prediction of pressure, and a single deep learning model of the whole GCS process including the cumulative injection volume of CO 2 as a deep learning feature, leads to the most accurate prediction of CO 2 saturation. For the post-injection period, it is key to use cumulative CO 2 injection volume to inform the deep learning models about the total carbon storage when predicting either pressure or saturation. The deep learning workflow not only provides high predictive fidelity across temporal and spatial scales, but also offers a speedup of 250 times compared to full physics reservoir simulation, and thus will be a significant predictive tool for engineers to manage the long-term process of GCS.

58 GEOSCIENCES↗
DOE OSTI2020

Production of Cf-252 and other transplutonium isotopes at Oak Ridge National Laboratory

In 1957 Glenn T. Seaborg conceived and advocated for the construction of the High Flux Isotope Reactor (HFIR) and the Transuranium Processing Plant (since then renamed the Radiochemical Engineering Development Center, or REDC) at Oak Ridge National Laboratory. There, heavily shielded hot cells, glove boxes, and laboratories allow recovery of transuranium elements produced in substantial quantities. Seaborg’s vision of HFIR and REDC producing milligram quantities of berkelium, californium, and einsteinium has been fulfilled beginning in 1966 through May 2019 with 78 production campaigns yielding a cumulative totals of 1.2 g of 249 Bk, 10.2 g of 252 Cf, 39 mg of 253 Es, and 15 pg of 257 Fm. Notably, 252 Cf is a neutron source used in many industrial applications including oil exploration; process control systems for the cement industry, coal analysis, and power production; sources to start nuclear reactors and perform nondestructive materials analyses; homeland security and national defense detection devices; and medical research. Isotopes made available through transplutonium production at HFIR/REDC have enabled scientists to study the nuclear properties and reactions, chemical properties, optical properties, and solid-state properties of transplutonium elements. Long-lived isotopes have served as targets in heavy ion accelerators to produce heavier elements leading to the discovery of 104 Rf, 105 Db, 106 Sg, 113 Nh, 114 Fl, 115 Mc, 116 Lv, 117 Ts, and 118 Og. This paper reviews the evolution of the processing flowsheets to produce, separate, and purify transplutonium isotopes, which have evolved over 50 years of operation at HFIR and REDC, and summarizes directions of future work to improve the efficiency of the production operations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

Na + -gated nanochannel membrane for highly selective ammonia (NH 3 ) separation in the Haber-Bosch process

Currently, cryogenic condensation is the predominant process for recovering ammonia (NH 3 ) in the Haber-Bosch (HB) process, which is highly energy intensive. To be more compatible with the reaction conditions in the HB process and thus minimize the pressure and temperature swing during reactant recycling, energy-efficient technologies for NH 3 extraction at elevated temperature and pressure are greatly needed. In this work, the Na + -gated nanochannel membrane, shown exclusively for water conduction in our previous work, also exhibited highly NH 3 -selective performance, with NH 3 /H 2 selectivity as high as 4,280 and NH 3 /N 2 selectivity > 10,000 at temperature up to 250 °C and pressure up to 35 bar. Excellent stability of the Na + -gated nanochannel membrane was demonstrated during a 100-h run in ternary NH 3 /H 2 /N 2 gas mixture at 200 °C and 35 bar, consistent with structural characterization by X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and Fourier transfer infrared (FTIR) spectroscopy. A techno-economic analysis (TEA) was conducted for the HB process using the Na + -gated nanochannel membrane and the traditional HB process with condenser. Finally, under the optimized separation conditions, > 80% energy savings and approximately 20% reduction of the net NH 3 production cost can be achieved, demonstrating the great potential of the Na + -gated nanochannel membrane for NH 3 separation in the HB process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Mixed matrix membranes for post-combustion carbon capture: From materials design to membrane engineering

Mixed matrix materials (MMMs) containing nanofillers dispersed in continuous polymer matrices have emerged as an exciting and versatile platform to develop membranes with superior CO 2 /N 2 separation performance for post-combustion carbon capture. Both polymers and nanofillers can be vertically designed and engineered to combine the advantages of excellent processability (derived from polymers) and strong size-sieving ability or/and significant permanent porosity (originated from nanofillers). However, the MMMs face major challenges, such as interfacial incompatibility, particle agglomeration, and poor thin-film formability. This report provides a comprehensive yet critical review of various polymers and nanofillers (such as metal-organic frameworks, covalent organic frameworks, and two-dimensional materials) with promising CO 2 /N 2 separation properties. We exhaustively describe strategies to improve interfacial compatibility, such as in situ syntheses of polymers and nanofillers and functionalization of both components to improve adhesion. Moreover, we highlight various approaches to engineer the MMMs into thin-film composite (TFC) membranes. The review reveals the structure/property relationship in these MMMs and outlines the challenges and opportunities to realize their potential for practical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

In-cylinder spray evolution in a motored central-injection gasoline engine: Imaging and simulating the effects of flash-boiling and intake crossflow

Accurate predictions of fuel spray behavior and mixture formation in simulations of direct-injection spark-ignition (DISI) engines are fundamental to ensure proper description of all subsequent processes including ignition, combustion, and emissions. In this work, the spray evolution in a single-cylinder optical DISI engine was studied experimentally and numerically with the goal of enabling predictive computational fluid dynamics (CFD) modeling of in-cylinder sprays. The authors explored a wide range of operating conditions characterized by several fuel injection temperatures and engine speeds, using a well-characterized nine-component gasoline surrogate known as PACE-20. The effect of flash boiling and intake crossflow on the spray is discussed, with a focus on evaluating the ability of the spray models to capture highly transient spray behavior. In the experiments, the fuel temperature was varied between 20°C and 80°C, allowing for non-flash- to flash-boiling transition to emerge with enhanced flashing intensity at the highest temperatures. Spray collapse resulted in vapor-rich regions, owing to the locally lower inertia of the fluid. Varying the engine speed from 650 to 1950 rpm promoted increasingly more turbulent in-cylinder crossflow which interacted with the spray during the injection event and resulted in enhanced spray dispersion. The CFD model was able to capture the spray morphology transition at different fuel temperatures and engine speeds adequately. Further, it is shown that the spray breakup model could capture the transitional spray behavior induced by flash boiling atomization and intake flow via proper initialization of the spray cone angle and calibration of the spray models’ constants.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Autonomous System Subversion Tactics: Prototypes and Recommended Countermeasures

One of the fielding requirements for Advanced and Small Modular Reactors (AR/SMR) is the ability to support remote and autonomous operations. Autonomous Control Systems (ACS) are found on platforms such as Autonomous Space Vehicles, Cruise Missiles, and advanced driver-assistance systems. Each of these ACS implementations depends upon a set of decision support subsystems responsible for supporting Autonomous Mission Managers (names vary based upon field and author preferences). These Autonomous Mission Managers receive inputs from system sensors (e.g., LIDAR collection from an automobile travelling down a street; transients from a nuclear reactor), and perform a set of classifications (e.g., Red Traffic Light; Small Pedestrian at 10m; Load Rejection; Single Coolant Pump Trip), and then use these classifications in combination with recommendation algorithms to achieve platform goals (e.g., Stop the Vehicle at the Traffic Light, Avoid the Small Pedestrian; Trip the Reactor to prevent a Safety Event). The design, implementation, and fielding of an ACS capability will alter the cyber-attack surface such that existing risk management plans will need to be updated to include how to protect and defend against data-science and decision-support-system attack classes. These attack classes would include protection of the design and training environments where algorithm selection and testing and training data would be obvious attack vectors. These attack classes would also require an informed set of detection and response procedures to identify anomalous behaviors and document best practices for anomaly assessment and vulnerability mitigation and remediation. Last year we published a Cyber Threat Assessment Methodology for Autonomous and Remote Operations for AR/SMRs along with a companion publication on Cyber Attack and Defense Use Cases. The focus of the methodology was on describing and enumerating ACS processes, components, and functions such that security engineers could: evaluate subversion options against the target; identify threat actor attributes and capabilities derived from each subversion option; and identify security controls and response countermeasures. The Use Cases document offered detailed methodology examples including an assessment of a Military Base SMR, an Autonomous System Decision Loop, and implementation of AR/SMR Machine Learning algorithms. Our proposal at the end of last year was to focus on implementation of subversion prototypes related to the last Use Case area: AR/SMR Machine Learning (ML) Algorithms. We included six attack scenarios in our Use Cases paper: a Poisoning Attack against ML functions implemented using an FPGA; a Trojaning Attack against ML classifiers exploiting the excitability of Nuclear Engineers; a Backdooring Attack against ML Training environments to ensure persistence of an attack vector; a False Positive Evasion Attack against multi-factor Access Control Systems using clever inputs; an Inference Attack against ML models by an Insider with access to the Operational environment; and an Adversarial Reprogramming Attack against a Material Access Control Video Surveillance System. At the beginning of this year these six attack scenarios were provided to our research teams at Georgia Tech and Idaho State University and each team successfully implemented a subversion attack against a ML implementation to include transient misclassifications. While this is a notable outcome from this type of research, this paper offers the reader insight into not only how to structure and execute these types of attacks, but into the thought process behind how the researcher investigated the problem space, performed initial algorithm implementation, and the trial-and-error behind arriving at the successful subversion prototypes. We include in this paper a set of associated Scenarios on how these subversion prototypes could be implemented and an initial set of guidance for AR/SMR architects, Nuclear Regulators, and Cyber Defenders to implement awareness and defense capabilities into their current operational portfolios.

42 ENGINEERING↗
DOE OSTI2023

Distributed Ledger Technology for Fault Tolerant Distribution Grid Operations

This paper explores the potential of distributed ledger technology (DLT) to improve fault-tolerant grid operations by leveraging its core features as an immutable, decentralized ledger, a distributed, consensus-based agreement process, and a distributed state-replication engine. Distribution power systems deliver electricity to millions of customers; however, they are susceptible to various threats that can result in customer interruptions. These include faults caused by adverse weather conditions, natural disasters, vegetation growth, equipment failure, and malicious attacks. To minimize the effects of these faults, fault-handling approaches rely on network knowledge to isolate affected areas and reconnect unaffected areas, reducing the number of affected customers while maintaining safety. Here, we present a trusted data-sharing architecture that enables independent, distributed actors to reconstruct the pre-fault system state by enabling distributed resources to make appropriate decisions with limited network/system information. Although the process requires some data sharing between switch-delimited areas, the approach limits the amount of private information shared, preserving customers' privacy and business-sensitive information. We include three use cases that form a foundation for third parties to develop functional solutions that can eventually be deployed in the field. The gross error detection method used within switch-delimited areas can identify sensor errors and accurately detect circuit breaker states. The evaluation of possible reconnection while preserving data ownership resulted in a voltage magnitude difference smaller than 0.001% from the OpenDSS power flow solution that has full system knowledge, which is below the expected power flow tolerance. The approach offers a promising opportunity for improving fault-tolerant distribution grid operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Effects of water addition on the combustion of iso -octane investigated in laminar flames, low-temperature reactors, and an HCCI engine

In this work, the effect of H 2 O injection on the combustion process of iso -octane was investigated with the aim to better understand the suitability of water addition as a potential engine control parameter for homogeneous-charge compression ignition (HCCI) combustion. Several experiments were combined including premixed low-pressure flames, a jet-stirred reactor (JSR) and a plug-flow reactor (PFR), both at atmospheric pressure, and a single-cylinder research engine (SCRE) operated with either iso -octane or RON 98 gasoline. The thermal effect of H 2 O addition was determined in laminar premixed iso -octane/O 2 /Ar flames (equivalence ratio $Φ$=1.4, 40 mbar) with H 2 O mole fractions of 0 to 0.22, where water addition reduced the temperature measured by laser-induced fluorescence (LIF) by up to 110 K. Speciation data were obtained from these flames as well as in the JSR ($Φ$=0.65, 933 mbar) and PFR experiments ($Φ$=0.65, 970 mbar) with and without H 2 O addition in the low- to intermediate temperature regime from 700–1100 K. The chemical analysis in these flame and reactor experiments was performed using molecular-beam mass spectrometry (MBMS) employing either electron ionization (EI) in the PFR and premixed flame or single-photon ionization (PI) by tunable vacuum-ultraviolet radiation in the JSR. The effects on species mole fractions were small which is supported by predictions from chemical-kinetic simulations. Quantitative speciation data of the exhaust gas of the SCRE were obtained by using Fourier-transform infrared (FTIR) spectroscopy. A very similar species pool was detected in the laboratory-scale experiments and for the engine operation. It is thus assumed that these results could assist in guiding both the improvement of fundamental chemical-kinetic as well as HCCI engine control models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Phase transition in two-dimensional monolayer (1L)-molybdenum disulfide induced by atomic S-basal plane gliding via synchrotron X-ray monochromatic beam radiation for superior electronic performance

Here, in this work, we report a novel approach to reduce the channel resistance by inducing a phase transition behavior from 2H to 1T in a monolayer MoS 2 (1L-MoS 2 ) by a synchrotron X-ray monochromatic beam (mono-beam) radiation. The effects of the biphase structure by the mono-beam on the 1L-MoS2 film were investigated using Raman spectra, photoluminescence (PL) spectra, scanning tunneling microscopy, and scanning tunneling spectroscopy, respectively. Through material characterization, we identified that the lateral sliding of S-vacancies along the S-plane in the 1L-MoS 2 is the key reason for the origin of unidirectional phase transition. The precise phase engineering triggered by the mono-beam radiation process allows the realization of field-effect transistors (FET) with 2X improvement in mobility toward a high on/off ratio (~10 8 ) and a near-ideal subthreshold swing of ~88 mV per decade. The validity of the phase engineering could be further extended for its application as a memory device, exhibiting a gate tunable conduction modulation behavior and a high resistance ratio of ~10 2 at a gate bias of 5 V with endurance of ~100 cycles. Furthermore, an artificial neural network using the synaptic weight update with accuracy of ~93 % was achieved.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

Abstract Background Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. Methods We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Results Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. Conclusion The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Orbital engineering of C 3 N monolayer to design efficient synergistic sites electrocatalyst for boosting alkaline hydrogen evolution

Alkaline water electrolyzer (AWE) is one of the promising technologies for hydrogen production at the industrial level. However, energetic inefficiency and low current density impede the development of AWE. Compared with acidic conditions, the Volmer step in alkaline hydrogen evolution reaction (HER) involves extra water dissociation, whose barrier is one of the most vital reasons for the sluggish kinetics of alkaline HER. Herein, choosing C 3 N monolayer as an ideal theoretical model, we design several empty orbitals through intentional metal doping, and further construct synergistic sites on the C 3 N monolayer to accelerate both water dissociation and hydrogen adsorption for alkaline HER. Furthermore, the as-designed Be-doped and Cr-doped C 3 N monolayers exhibit rather low theoretical overpotential of 0.476 eV and 0.216 eV for alkaline HER, respectively, which are even lower than Pt (1 1 1) surface. Moreover, by comparing the water dissociation behaviors on metal-doped C3N monolayer, we find that the empty orbitals with suitable orientation and energy level are useful for promoting the water dissociation process, indicating that we can use orbital engineering strategy to regulate the adsorption strength between adsorbate and surface site. Consequently, it is reasonable to suggest that our orbital engineering strategy would significantly benefit the design of highly efficient alkaline HER electrocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Exploring Engine Oil Reactivity Effects on End Gas Knock in a Direct-Injection Spark Ignition Engine

An experimental study was conducted in a direct-injection (DI) spark-ignited engine to determine the extent to which oil reactivity impacts combustion phasing and knock propensity. Three engine oils were examined: a baseline 20W30 oil from conventional base stock, a 5W30 oil from a synthetic base stock, and a jet oil from a hindered ester base stock. The engine was operated at a constant fueling rate of 24.7 mg/injection for two engine speed conditions (1500 and 2000 rpm) using two cam profile conditions (high and low lift), for a total of four operating conditions. Spark timing sweeps were conducted at each of the four operating conditions. Results were analyzed for an engine oil impact on combustion phasing, cycle-to-cycle variability, combustion duration, knock propensity, and knock intensity. No correlation between engine oil type and any of these performance metrics could be identified. Measurements showed that the oil consumption rate for this engine is low and comparable to engines compliant with U.S. Tier 1 and Tier 2 emissions standards, consuming 1.4 g/kg of fuel consumed (150 g for 20 hours of operation). Finally, the lack of a correlation between the oil type and engine performance can be attributed to this low level of oil consumption, resulting in very little interaction between the oil and the combustion chamber contents.

42 ENGINEERING↗
DOE OSTI2018

Development of Hot-Isostatic Pressing for Treatment of UK ILW Radioactive Wastes - 18280

Hot-Isostatic Pressing (HIPing) has been proposed as an improved method for the treatment of radioactive wastes in the UK. Sludges and slurries housed on the Sellafield site are a prime candidate for HIP treatment due to their large volumes and issues associated with the use of the baseline cementation strategy. Options have been developed by GeoRoc Ltd to co-process these wastes, including a detailed conceptual plant design. This paper will describe research and development aimed at demonstrating the viability of the concept presented in this design. This paper summarizes two studies performed to address the knowledge gaps identified for treatment of these wastes using HIP technology. The first study related to the poorly characterized nature of the wastes, which requires any treatment option to be flexible in terms of the chemical and physical properties of the waste feed. The second study involved demonstrating that HIPing can be effectively utilized at a scale applicable to treat a waste inventory estimated to be in excess of 5,000 m{sup 3}. The first section of this paper presents a summary of research carried out to determine where variation in the waste stream composition may affect the processing and wasteform produced when HIPing Magnox sludges. This study aimed to qualify where restrictions on the process envelope may exist due to poorly defined waste-stream characteristics. A baseline wasteform was selected with the aim of achieving significant waste volume reduction, while producing a physically and chemically stable wasteform. A glass-bonded magnesium-titanate/magnesium-silicate wasteform was selected as the preferred option for the Magnox sludge wastes. A series of studies investigated the densification and phase formation of waste-forms by altering key variables in the Magnox sludge simulant. To test the extremes of the processable waste loading, samples were produced and characterized at 100 wt% waste-loading for Magnox sludge, Site-Ion Exchange Plant (SIXEP) sand/clinoptilolite and a 50:50 mix of the two waste-streams. Further studies involved a) altering the waste loading to additive mass ratio (to simulate changes in the waste loading/sludge solids content), b) varying the particle size distribution from the datum to include only small or large particulates in the sludge feed; and c) introducing up to 20 wt% metallic Magnox alloy, organic species or carbonate materials (to determine how their inclusion may affect the processing and densification of the materials). A U{sub 3}O{sub 8} loaded sample was also produced using the baseline Magnox sludge formulation. All the tests performed were shown to produce monolithic, well densified waste-forms with substantial volume reductions. Minimal variations from the baseline were noted but the waste-forms produced with these deviations was determined to be of comparable quality to of the baseline product. U{sub 3}O{sub 8} was shown to behave in a similar fashion to the ZrO{sub 2} surrogate used to simulate it in the process envelope studies and was encapsulated in the magnesium titanate/magnesium silicate matrix. This work demonstrates that HIP technology can successfully produce waste-forms across the broad process envelope expected in the Magnox sludge inventory. It is also possible to produce monolithic waste-forms at 100 wt% waste loading from Magnox sludges, SIXEP sand clinoptilolite slurries or a co-processed mixture of the two. The second part of this paper summarizes a commercially relevant demonstration of HIP technology for the treatment of sludge and slurry wastes housed at the Sellafield site (UK). This study culminated in production of the largest HIPed wasteform successfully produced to date. This study was performed in a series of stages. Investigations into formulation and properties of waste-forms were performed at a lab scale to evaluate suitable wasteform systems and identify suitable combinations of additives and waste loadings. Scale up demonstrations were then performed in stages with custom-designed HIP canisters. Scale-up and characterization of key wasteform properties were successfully performed with initial canister volumes of 50 ml, 400 ml and 8 L. Suitable front-end unit operations to produce a granular, free-flowing calcined simulant were demonstrated at an engineering scale. The demonstration was successful in processing a HIP canister with an initial starting volume in excess of 100 L. A 75 % volume reduction from the raw sludge was achieved at scale while demonstrating that HIP is applicable at suitably large scale for immobilization of ILW waste. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

ENERGY SOURCES AND LIGHT CURVES OF MACRONOVAE

A macronova (kilonova) was discovered with a short gamma-ray burst, GRB 130603B, which is widely believed to be powered by the radioactivity of r-process elements synthesized in the ejecta of a neutron star (NS)–binary merger. As an alternative, we propose that macronovae are energized by the central engine, i.e., a black hole or NS, and the injected energy is emitted after the adiabatic expansion of ejecta. This engine model is motivated by extended emission of short GRBs. In order to compare the theoretical models with observations, we develop analytical formulae for the light curves of macronovae. The engine model allows a wider parameter range, especially smaller ejecta mass, and a better fit to observations than the r-process model. Future observations of electromagnetic counterparts of gravitational waves should distinguish energy sources and constrain the activity of the central engine and the r-process nucleosynthesis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

A Workshop on the History of Plutonium Processing at Hanford Washington as the Foundation for Modern-day Plutonium Process Science

Numerous national laboratories in the United States have roots related to the Manhattan Project that contributed to the end of World War II. The pioneering science and engineering that took place over the decades that followed continues to influence modern-day actinide-related research at those institutions, leading to unique strengths and cutting-edge ideas and perspectives. These same national laboratories also face a challenge: figuring out how to capture the expertise of a retiring workforce who had first-hand experience in these pioneering nuclear efforts. Recently, at PNNL a “Train-the-Trainer” approach has been piloted where mentors and mentees are paired together to develop and deliver interactive workshops on historical topics that relate to modern-day research, such as Plutonium Processing or Environmental Management of Legacy Nuclear Waste. This approach was used to develop a workshop that beings with the Historic Hanford process plutonium chemistry and engineering, describes its influence on current plutonium separation and process science, and then details the chemistry of plutonium as it progresses from a minor constituent in irradiated fuel to purified solid product. This workshop is targeted to the practitioner of applied science and technology wishing to gain a better understanding of the history and process-related chemistry of element 94 so that they may better direct the tools of their specific craft toward the present and future needs of plutonium science.

Smith, Frances N.↗
DOE OSTI2018

Modeling of Powder Bed Manufacturing Defects

Powder bed additive manufacturing offers unmatched capabilities. The deposition resolution achieved is extremely high enabling the production of innovative functional products and materials. Achieving the desired final quality is, however, hampered by many potential defects that have to be managed in due course of the manufacturing process. Defects observed in products manufactured via powder bed fusion have been studied experimentally. In this effort we have relied on experiments reported in the literature and—when experimental data were not sufficient—we have performed additional experiments providing an extended foundation for defect analysis. There is large interest in reducing the effort and cost of additive manufacturing process qualification and certification using integrated computational material engineering. A prerequisite is, however, that numerical methods can indeed capture defects. A multiscale multiphysics platform is developed and applied to predict and explain the origin of several defects that have been observed experimentally during laser-based powder bed fusion processes. The models utilized are briefly introduced. The ability of the models to capture the observed defects is verified. The root cause of the defects is explained by analyzing the numerical results thus confirming the ability of numerical methods to provide a foundation for rapid process qualification.

36 MATERIALS SCIENCE↗
DOE OSTI2014

ActiveSpaces: Exploring dynamic code deployment for extreme scale data processing: ActiveSpaces: Exploring dynamic code deployment for extreme scale data processing

Managing the large volumes of data produced by emerging scientific and engineering simulations running on leadership-class resources has become a critical challenge. The data have to be extracted off the computing nodes and transported to consumer nodes so that it can be processed, analyzed, visualized, archived, and so on. Several recent research efforts have addressed data-related challenges at different levels. One attractive approach is to offload expensive input/output operations to a smaller set of dedicated computing nodes known as a staging area. However, even using this approach, the data still have to be moved from the staging area to consumer nodes for processing, which continues to be a bottleneck. In this paper, we investigate an alternate approach, namely moving the data-processing code to the staging area instead of moving the data to the data-processing code. Specifically, we describe the ActiveSpaces framework, which provides (1) programming support for defining the data-processing routines to be downloaded to the staging area and (2) runtime mechanisms for transporting codes associated with these routines to the staging area, executing the routines on the nodes that are part of the staging area, and returning the results. We also present an experimental performance evaluation of ActiveSpaces using applications running on the Cray XT5 at Oak Ridge National Laboratory. Finally, we use a coupled fusion application workflow to explore the trade-offs between transporting data and transporting the code required for data processing during coupling, and we characterize sweet spots for each option.

97 MATHEMATICS AND COMPUTING↗