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All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

The Extragalactic X-ray Background in the 0.2 - 2 keV Range

We made the first measurement of the extragalactic 0.7 keV background. We detected the X-ray shadow of a neutral gas cloud in the Magellanic Bridge. We further constrained the point-like source contribution based on the mean spectrum of detected sources and on our early autocorrelation function analysis of the background. We find that our measurement extragalactic background intensity is significantly greater than the total point-like source contribution expected if sources are responsible for all the observed background intensity in the 1-2 keV range. For a further confirmation of the theoretical prediction of the hot intergalactic medium, we have conducted a pilot project to search for enhanced X-ray-emitting features near rich clusters of galaxies. We have reported the discovery of an elongated complex of extended X-ray-emitting objects in and around the galaxy cluster A2125, based on an archival deep ROSAT/PSPC observation. Using multicolor optical imaging of galaxies in the field, we find that this complex represents a hierarchical superstructure spanning approx. 11 Mpc at the redshift approx. 0.247. The multiple peak X-ray morphology and large blue galaxy fraction of A2125 indicate that the cluster is undergoing a coalescence of subunits. The superstructure contains two additional clusters, projected at distances of only 3 and 4.3 Mpc from A2125. The most interesting feature is, however, the low-surface-brightness X-ray emission from a moderate galaxy concentration away from individual clusters. The emission likely arises in a hot (approx. 10(exp 7) K) intergalactic medium, as predicted in N-body/hydro simulations of structure formation. These results demonstrate the potential of X-ray observations as a powerful tool to study the large-scale structure of the universe.

Wang, Q. Daniel↗
NASA NTRS2002

Direct-Drive Gas-Cooled Reactor Power System: Concept and Preliminary Testing

This paper describes the concept and preliminary component testing of a gas-cooled, UN-fueled, pin-type reactor which uses He/Xe gas that goes directly into a recuperated Brayton system to produce electricity for nuclear electric propulsion. This Direct-Drive Gas-Cooled Reactor (DDG) is designed to be subcritical under water or wet- sand immersion in case of a launch accident. Because the gas-cooled reactor can directly drive the Brayton turbomachinery, it is possible to configure the system such that there are no external surfaces or pressure boundaries that are refractory metal, even though the gas delivered to the turbine is 1144 K. The He/Xe gas mixture is a good heat transport medium when flowing, and a good insulator when stagnant. Judicious use of stagnant cavities as insulating regions allows transport of the 1144-K gas while keeping all external surfaces below 900 K. At this temperature super-alloys (Hastelloy or Inconel) can be used instead of refractory metals. Super-alloys reduce the technology risk because they are easier to fabricate than refractory metals, we have a much more extensive knowledge base on their characteristics, and, because they have a greater resistance to oxidation, system testing is eased. The system is also relatively simple in its design: no additional coolant pumps, heat exchanger, or freeze-thaw systems are required. Key to success of this concept is a good knowledge of the heat transfer between the fuel pins and the gas, as well as the pressure drop through the system. This paper describes preliminary testing to obtain this key information, as well as experience in demonstrating electrically heated testing of simulated reactor components.

Wright, S. A.↗
DOE OSTI2022

AI-Enabled Discovery and Physics-Based Optimization of Energy Efficient Processing Strategies for Advanced Turbine Alloys (Final Technical Report)

In this project, the multi-organizational team of academic and industrial researchers from the University of Kentucky an aerospace and energy generation OEM partner has leveraged novel Digital Process Twin (DPT) models of process/structure interactions (i.e., process-induced surface integrity) to advance a paradigm of fully integrated computational materials engineering (ICME). Using efficient process models as the core of a digital process simulator for a reinforcement learning algorithm, the team has integrated industrial data and metrics of structure/performance/energy relationships and manufacturing-related energy metrics to optimize dynamic processing parameters for significantly improved life-cycle energy efficiency of advanced γ-TiAl low-pressure turbine (LPT) alloys, as indicated by a set of design relevant parameters (e.g., residual stresses and scrap rate). The key objective and anticipated outcome of the project was at least a 10% reduction in life-cycle embodied energy for a recently developed, γ-TiAl low-pressure turbine (LPT) alloy and nickel-based superalloy Inconel 718, through the adoption of the proposed AI-enabled process optimization approach. The final project outcomes significantly exceeded this original target, realizing manufacturing-related energy efficiency improvements of more than 130% for TiAl and up to 80% for Inconel 718. Rather than following the prevailing and highly inefficient empirical paradigm, the proposed study demonstrated the feasibility of adopting a digital, physics-based process design and optimization paradigm. The recurring need for manual intervention, rework, reinspection causes significant production bottlenecks and unnecessary expense associated with delivering the requisite component quality. The OEM partner, and turbine industry in general, expect to reap significant cost and resource savings if an AI-optimized set of parameters can be applied to specific machining operations. The technical scope of the proposed project involved the paving of a realistic path towards model-based and AI-enabled Integrated Computational Materials Engineering (ICME), and away from inefficient empirical process optimization and legacy manufacturing practices, which are no longer able to efficiently process novel high-performance turbine alloy materials. The project team will address the fundamental knowledge gap that currently exists within the ICME paradigm with respect to the process/structure/performance/energy impacts of finishing processes. While significant resources have been devoted to the ‘early stages’ of manufacturing, such as alloy design, primary and secondary processing, finishing processes have not been adequately integrated within ICME. To provide an actionable path towards model-based finishing process design (e.g., machining, burnishing, grinding, polishing), we will employ a novel AI-enabled process optimization paradigm, based on a computationally efficient, physics-based process simulator. Through limited experimental work to calibrate and validate our process simulator model via an advanced in-situ characterization technique and process optimization via reinforcement learning, the project will seek to demonstrate a viable alternative to the inefficient ‘legacy’ processing strategies, empirical testing and broad scope machining learning approaches, all of which fail to adequately consider complex process physics. The project team has identified an intermetallic γ-TiAl LPT alloy, which is currently being used as part of the OEM partner’s advanced gas turbine designs. This particular alloy poses significant manufacturing challenges during finishing operations, which limit the degree to which the current turbine design can be manufactured in an energy- and cost-efficient manner. Empirical testing and numerical modeling efforts to optimize processing parameters for γ-TiAl have not been able to resolve these manufacturing challenges, so the proposed physics-based AI-enabled optimization technology would offer a truly novel and transformative capability. The multi-organizational team of academic and industry experts from the UKY and the OEM partner will work together closely to demonstrate the analytical and experimental critical function and characteristic proof of concept of this novel approach.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2000

The Finer Details: Climate Modeling

If you want to know whether you will need sunscreen or an umbrella for tomorrow's picnic, you can simply read the local weather report. However, if you are calculating the impact of gas combustion on global temperatures, or anticipating next year's rainfall levels to set water conservation policy, you must conduct a more comprehensive investigation. Such complex matters require long-range modeling techniques that predict broad trends in climate development rather than day-to-day details. Climate models are built from equations that calculate the progression of weather-related conditions over time. Based on the laws of physics, climate model equations have been developed to predict a number of environmental factors, for example: 1. Amount of solar radiation that hits the Earth. 2. Varying proportions of gases that make up the air. 3. Temperature at the Earth's surface. 4. Circulation of ocean and wind currents. 5. Development of cloud cover. Numerical modeling of the climate can improve our understanding of both the past and, the future. A model can confirm the accuracy of environmental measurements taken. in, the past and can even fill in gaps in those records. In addition, by quantifying the relationship between different aspects of climate, scientists can estimate how a future change in one aspect may alter the rest of the world. For example, could an increase in the temperature of the Pacific Ocean somehow set off a drought on the other side of the world? A computer simulation could lead to an answer for this and other questions. Quantifying the chaotic, nonlinear activities that shape our climate is no easy matter. You cannot run these simulations on your desktop computer and expect results by the time you have finished checking your morning e-mail. Efficient and accurate climate modeling requires powerful computers that can process billions of mathematical calculations in a single second. The NCCS exists to provide this degree of vast computing capability.

Source record↗
NASA NTRS2004

Sensory-Feedback Exoskeletal Arm Controller

An electromechanical exoskeletal arm apparatus has been designed for use in controlling a remote robotic manipulator arm. The apparatus, called a force-feedback exoskeleton arm master (F-EAM) is comfortable to wear and easy to don and doff. It provides control signals from the wearer s arm to a robot arm or a computer simulator (e.g., a virtual-reality system); it also provides force and torque feedback from sensors on the robot arm or from the computer simulator to the wearer s arm. The F-EAM enables the wearer to make the robot arm gently touch objects and finely manipulate them without exerting excessive forces. The F-EAM features a lightweight design in which the motors and gear heads that generate force and torque feedback are made smaller than they ordinarily would be: this is achieved by driving the motors to power levels greater than would ordinarily be used in order to obtain higher torques, and by providing active liquid cooling of the motors to prevent overheating at the high drive levels. The F-EAM (see figure) includes an assembly that resembles a backpack and is worn like a backpack, plus an exoskeletal arm mechanism. The FEAM has five degrees of freedom (DOFs) that correspond to those of the human arm: 1. The first DOF is that of the side-to-side rotation of the upper arm about the shoulder (rotation about axis 1). The reflected torque for this DOF is provided by motor 1 via drum 1 and a planar four-bar linkage. 2. The second DOF is that of the up-and-down rotation of the arm about the shoulder. The reflected torque for this DOF is provided by motor 2 via drum 2. 3. The third DOF is that of twisting of the upper arm about its longitudinal axis. This DOF is implemented in a cable remote-center mechanism (CRCM). The reflected torque for this DOF is provided by motor 3, which drives the upper-arm cuff and the mechanism below it. A bladder inflatable by gas or liquid is placed between the cuff and the wearer s upper arm to compensate for misalignment between the exoskeletal mechanism and the shoulder. 4. The fourth DOF is that of flexion and extension of the elbow. The reflected torque for this DOF is provided by motor 4 and drum 4, which are mounted on a bracket that can slide longitudinally by a pin-and-slot engagement with the upper-arm cuff to compensate for slight variations in the position of the kinematic center of the elbow. Attached to drum 4 is an adapter plate to which is attached a CRCM for the lower arm. 5. The lower-arm CRCM implements the fifth DOF, which is the twist of the forearm about its longitudinal axis. Motor 5 provides the reflected torque for this DOF by driving the lower-arm cuff. A rod transmits twist and torsion between the lower-arm cuff and the hand cuff. With this system, the motion of the wearer s joints and the reflected torques applied to these joints can be measured and controlled in a relatively simple manner. This is because the anthropomorphic design of the mechanism imitates the kinematics of the human arm, eliminating the need for kinematic conversion of joint-torque and joint-angle data.

An, Bin↗
DOE OSTI2025

Radiation damage effects in beryllium for next generation neutrino beam targetry (Final Technical Report)

Current and future high-power accelerators put severe requirements on materials used for target and beam windows and target facilities have been recognized as a critical challenge in development of future particle accelerators. In accelerators, window and target materials are exposed to extreme conditions, which include bombardment with very high energy protons (1- 100 GeV) and thermomechanical shock waves. Radiation can cause direct damage in the material, and it leads to production of transmutation products (especially helium), both phenomena having a potential adverse effect on the stability and durability of the target/window material. At high enough temperatures, He can aggregate to form gas bubbles, which in turn cause significant dimensional changes (swelling), enable easy crack propagation, and eventually cause failure by fracture. On the other hand, if the temperature is too low, radiation damage accumulates in the form of internal defects (e.g., dislocations), leading to hardening and a decreased ductility of the material. In this project, we will focus on beryllium since it is considered to be one of the candidate materials for beam windows and targets in the next-generation proton accelerators, e.g., the Long Baseline Neutrino Facility (LBNF). Radiation effects in Be have been studied in the context of nuclear fusion reactor applications. However, key differences exist between reactor and accelerator conditions, including neutron vs. proton irradiation, continuous vs. pulsed beam flux, much higher energies of bombarding particles in accelerators, and higher operating temperatures for typical reactors. For example, the impact of beam pulsing on the radiation damage and the He bubble kinetics is largely unknown. While results obtained on Be from fusion research might not be directly transferrable to understanding target materials, there is an opportunity to bring state-of-the-art tools from materials research in nuclear reactors to aid design of target and beam window materials in high-power accelerators. To this end, the overarching goal of this project are to develop an experimentally-validated computational framework capable of predicting radiation damage evolution in beryllium relevant to beam window and target conditions, focusing on He bubble formation and growth as a function of irradiation temperature. Our model will be based on the cluster dynamics formalism, where size distribution of defects and He bubbles is simulated as a function of time, temperature, and radiation dose. Parameters for the model will be taken from published experiments and from high-fidelity atomistic simulations proposed in this project. In addition, we will carry out a series of targeted ex-situ and in-situ dual-beam experiments using low-energy protons to provide critical data for validation of the model on the effects of radiation on He clustering, He bubble distribution, and dislocation loop density/size in proton irradiated Be.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deep Analysis Net with Causal Embedding for Coal-fired Power Plant Fault Detection and Diagnosis (DANCE4CFDD)

Fault detection and diagnosis is critical to power plant operation to ensure attaining high reliability while reducing operation cost. As more renewable power is introduced to the power grid, traditional fossil power plants take on the extra burden of excessive load cycling to compensate the generation variability from renewable power. Such load cycling will pose more reliability challenges to power plant operation. There are a number of challenges faced by today’s asset health management system in coal- fired (or gas) power plants: 1) high-dimensional nonlinear interaction among multiple time series measurements; 2) high measurement variance induced by operational conditions/modes; 3) variation among asset types and plant configurations; and 4) a small number of faulty events to learn from. To cope with these challenges, today’s fielded asset health management systems rely heavily on manual efforts from domain experts and hand-crafted features or rules based on domain knowledge. Despite its role in plant reliability, such a practice is costly and hinders its scalability and sustainability, particularly when a plant undergoes modifications. The objective of this project is to develop a novel end-to-end AI learning system that is trainable (i.e., the AI representation of a complex system behavior can be directly learned from properly labeled data) for accurate fault detection and root cause analysis. The ability to create a fault detection model directly from time series could alleviate the efforts associated with today’s asset management solution development. In the course of this project, we have achieved the following: Created an AI model development environment incorporating state-of-the-art neural network architectures for rapid model development and evaluation; Developed novel learning strategies for training of fault detection model; Developed special-purpose neural network architecture embedded with variable association graph aiming for better interpretability; Developed a learning strategy to leverage a small number of faulty events for enhanced fault detection capability; Conducted detailed experimental study based on public benchmark datasets and demonstrated the effectiveness of the proposed solution; and Validated the developed system with data from both a coal-fired plant boiler dynamic simulation model and real-world coal-fired power plant covering multiple asset and fault types. Overall, the project attained a technology readiness level of TRL 5 from TRL 2 at the beginning of the project.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1997

Evolution of Structure in the Intergalactic Medium and the Nature of the LY-Alpha Forest

We have performed a detailed statistical study of the evolution of structure in a photoionized intergalactic medium (IGM) using analytical simulations to extend the calculation into the mildly nonlinear density regime found to prevail at z = 3. Our work is based on a simple fundamental conjecture: that the probability distribution function of the density of baryonic diffuse matter in the universe is described by a lognormal (LN) random field. The LN distribution has several attractive features and follows plausibly from the assumption of initial linear Gaussian density and velocity fluctuations at arbitrarily early times. Starting with a suitably normalized power spectrum of primordial fluctuations in a universe dominated by cold dark matter (CDM), we compute the behavior of the baryonic matter, which moves slowly toward minima in the dark matter potential on scales larger than the Jeans length. We have computed two models that succeed in matching observations. One is a nonstandard CDM model with OMEGA = 1, h = 0.5, and GAMMA = 0.3, and the other is a low-density flat model with a cosmological constant (LCDM), with OMEGA = 0.4, OMEGA(sub LAMBDA) = 0.6, and h = 0.65. In both models, the variance of the density distribution function grows with time, reaching unity at about z = 4, where the simulation yields spectra that closely resemble the Ly-alpha forest absorption seen in the spectra of high-z quasars. The calculations also successfully predict the observed properties of the Ly-alpha forest clouds and their evolution from z = 4 down to at least z = 2, assuming a constant intensity for the metagalactic UV background over this redshift range. However, in our model the forest is not due to discrete clouds, but rather to fluctuations in a continuous intergalactic medium. At z = 3; typical clouds with measured neutral hydrogen column densities N(sub H I) = 10(exp 13.3), 10(exp 13.5), and 10(exp 11.5) /sq cm correspond to fluctuations with mean total densities approximately 10, 1, and 0.1 times the universal mean baryon density. Perhaps surprisingly, fluctuations whose amplitudes are less than or equal to the mean density still appear as "clouds" because in our model more than 70% of the volume of the IGM at z = 3 is filled with gas at densities below the mean value.

Bi, Hongguang↗
DOE OSTI2021

Total X-Ray Emission from the LMC Observed with HaloSat

We constrain the global parameters of the Large Magellanic Cloud (LMC) by modeling the first soft X-ray (0.4–6.8 keV) observations of the entire LMC produced in a single pointing with moderate spectral resolution by the HaloSat CubeSat. These data are best fit with the sum of two thermal plasma components in collisional ionization equilibrium and a power law. We find cool (0.210 ± 0.014 keV) and hot (0.89 ± 0.14 keV) components. The total X-ray luminosity of the LMC is (1.08 ± 0.14) × 10{sup 39} erg s{sup −1}. X-ray binaries make up a large fraction of the emission with a luminosity of (6.0 ± 0.8) × 10{sup 38} erg s{sup −1}, followed by cool gas from superbubbles, supernovae, and diffuse emission with a luminosity of (3.0 ± 0.3) × 10{sup 38} erg s{sup −1}. The hot gas from star formation contributes the smallest fraction, with a luminosity of (1.9 ± 0.5) × 10{sup 38} erg s{sup −1}. We estimate the total volume of the cool gas to be between (0.2–1.2) × 10{sup 10} pc{sup 3} and the hot gas to be between (1.0–5) × 10{sup 7} pc{sup 3} for filling factors of f = 1 and 0.2. These volumes result in a total thermal energy for the cool gas between (1.4–3) × 10{sup 54} erg for electron densities of 0.017–0.04 cm{sup −3}, and a thermal energy for the hot gas between (1.7–4) × 10{sup 53} erg for electron densities of 0.12–0.3 cm{sup −3}. This yields cooling timescales for the cool and hot gas of (1.5–3) × 10{sup 8} yr and (1.8–6) × 10{sup 7} yr, respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Nitrogen evolution, NO X formation and reduction in pressurized oxy coal combustion

Oxy-combustion is one of the most prominent solutions for reducing CO 2 emissions from coal-fired power plants using carbon-capture-and-utilization technology. However, when compared to air combustion at atmospheric pressure, oxy-combustion is very expensive, owing to the significant efficiency penalties associated with air separation, flue gas recirculation (FGR), treatment, compression, and storage or transit of CO 2 . In comparison, pressurized oxy-combustion (POC) is more efficient as it recovers a significant amount of heat energy from the flue gas moistures. Nevertheless, CO 2 derived from pressurized oxy coal combustion has impurities, e.g., acid gases (NO X and SO X ) that can corrode the plant equipment, transport lines as well as deteriorating effect on the environment. Fortunately, in pressurized combustion systems, both NO X and SO X can be scrubbed by a single-column direct contact cooler (DCC), but this requires a minimum ratio of NO X to SO X at the inlet to be efficiently removed. Therefore, NOx is one of the important hindering parameters in commercializing the pressurized oxy-combustion. Although NOx evolution during oxy-coal combustion has been explored extensively at 1 atm, higher pressure studies are rare. Much still needs to be done to better understand the NO X mechanism and the effects of different parameters on NO X emissions under these conditions. Here, this paper reviews the published literature on nitrogen evolution, NO X formation and reduction in pressurized oxy-coal combustion. At higher pressures, the NO X from fuel-bound nitrogen is generated through volatiles, tar and char, all of which are discussed. Where literature is not available, the effect of pressure on NOx evolution in different stages of coal combustion is predicted through CHEMKIN simulation. Homogeneous and heterogeneous pathways of NO X formation and their destruction in pressurized oxy-coal combustion are evaluated. Additionally, the effect of pressure on a few mature and commercialized NOx abatement methods is explored. In the last, the future perspective and recommendation are given. This review will aid in the provision of basic knowledge about NOx evolution and control in pressurized fuel combustion, as well as the identification of new research areas to pursue.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Testing of Helium-Cooled Metal Molybdenum Disk Target

NorthStar Medical Radioisotopes LLC is planning to produce an important medical radioisotope, molybdenum-99 (Mo-99), through photonuclear reaction on molybdenum-100 (Mo-100). In this approach, molybdenum metal will be bombarded with a 40-MeV electron beam. Because enriched Mo-100 is expensive, it is desired to use as much beam power as possible to achieve maximum production yield and minimize target mass. This objective leads to very high beam power density (heat deposition in the target), which sets challenging requirements for cooling. Together with scientists at Los Alamos National Laboratory, a team at Argonne National Laboratory has developed and demonstrated a cooling approach using pressurized helium, which allows for efficient heat removal. One of the main challenges in this approach is the management of the heat load on the target window. The target window separates the high-pressure helium inside the target from the vacuum in the beamline, so it is constantly under stress from differential pressure. Also, the window is cooled only by the helium gas flowing on one side, making the window cooling even more challenging. High heat deposition in the target disks also imposes a strict requirement on performance of the helium cooling system and thickness of the target disks. The target disks are produced from metal powder via a press-and-sinter process. The resulting disks do not possess tensile strength as high as solid molybdenum and might not survive the vibration from the high-velocity helium coolant and high thermal stress from beam heating. An Argonne team of scientists performed a series of tests at Argonne’s Low Energy Accelerator Facility (LEAF) [3-7]. This report describes two series of tests for scale down production target designs that utilize full-scale 29 millimeters diameter, 0.75 mm thick press-and-sintered disks. We performed two thermal tests with different beam parameters and configurations of the disk laminations. We compared the results of the window temperature measurements and cooling system parameters obtained in the experiments with those predicted by analytical calculations and Computation Flow Dynamic (CFD) simulations. Results of the experiments and calculations are presented below.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Dynamic projection of anthropogenic emissions in China: methodology and 2015–2050 emission pathways under a range of socio-economic, climate policy, and pollution control scenarios

Abstract. Future trends in air pollution and greenhouse gas (GHG)emissions for China are of great concern to the community. A set of globalscenarios regarding future socio-economic and climate developments, combiningshared socio-economic pathways (SSPs) with climate forcing outcomes asdescribed by the Representative Concentration Pathways (RCPs), was createdby the Intergovernmental Panel on Climate Change (IPCC). Chinese researchers have also developed various emission scenarios by considering detailed local environmental and climate policies. However, a comprehensive scenario set connecting SSP–RCP scenarios with local policies and representing dynamic emission changes under local policies is still missing. In this work, to fill this gap, we developed a dynamic projection model, the Dynamic Projection model for Emissions in China (DPEC), to explore China'sfuture anthropogenic emission pathways. The DPEC is designed tointegrate the energy system model, emission inventory model, dynamicprojection model, and parameterized scheme of Chinese policies. The modelcontains two main modules, an energy-model-driven activity rate projectionmodule and a sector-based emission projection module. The activity rateprojection module provides the standardized and unified future energyscenarios after reorganizing and refining the outputs from the energy systemmodel. Here we use a new China-focused version of the Global ChangeAssessment Model (GCAM-China) to project future energy demand and supply inChina under different SSP–RCP scenarios at the provincial level. Theemission projection module links a bottom-up emission inventory model, theMulti-resolution Emission Inventory for China (MEIC), to GCAM-China andaccurately tracks the evolution of future combustion and production technologiesand control measures under different environmental policies. We developedtechnology-based turnover models for several key emitting sectors (e.g.coal-fired power plants, key industries, and on-road transportationsectors), which can simulate the dynamic changes in the unit/vehicle fleetturnover process by tracking the lifespan of each unit/vehicle on an annualbasis. With the integrated modelling framework, we connected five SSP scenarios(SSP1–5), five RCP scenarios (RCP8.5, 7.0, 6.0, 4.5, and 2.6), and threepollution control scenarios (business as usual, BAU; enhanced controlpolicy, ECP; and best health effect, BHE) to produce six combined emissionscenarios. With those scenarios, we presented a wide range of China's futureemissions to 2050 under different development and policy pathways. We foundthat, with a combination of strong low-carbon policy and air pollutioncontrol policy (i.e. SSP1-26-BHE scenario), emissions of major airpollutants (i.e. SO 2 , NO x , PM 2.5 , and non-methane volatile organic compounds – NMVOCs) in China willbe reduced by 34%–66% in 2030 and 58%–87% in 2050 compared to 2015. End-of-pipe control measures are more effective for reducing air pollutant emissions before 2030, while low-carbon policy will play a more important rolein continuous emission reduction until 2050. In contrast, China's emissionswill remain at a high level until 2050 under a reference scenario without activeactions (i.e. SSP3-70-BAU). Compared to similar scenarios set from theCMIP6 (Coupled Model Intercomparison Project Phase 6), our estimates ofemission ranges are much lower than the estimates from the harmonized CMIP6 emissions dataset in2020–2030, but their emission ranges become similar in the year 2050.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Design and Optimization of a Fast-Switching Electromagnetic Valve Actuator for Off-highway Vehicle Hydraulic Systems

Electrification of off-highway vehicles offers improved efficiency and reduction in greenhouse gas emissions. However, the extremely low power densities of electric machines relative to the hydraulics used in conventional off-highway vehicles makes electrification challenging. Although the recently proposed Hybrid Hydraulic Electric Architecture (HHEA) can overcome this limitation, it requires frequent switching between the pressure rails using switching valves resulting in losses. Fast switching minimizes the switching losses in these valves, which otherwise significantly reduce the overall efficiency of the system. The primary contribution of this paper is the design and optimization of a linear electromagnetic actuator for a fast-switching valve. This paper identifies the actuator requirements to enable fast switching and presents a design and optimization technique to realize actuators that meet the design objectives. In addition, a multi-physics approach is proposed to model the performance of the complete switching valve by considering the electromagnetic, fluidic, and mechanical physics. An optimal actuator design is obtained using the developed optimization framework, and the multi-physics model demonstrates that the selected design achieves a 30% reduction in throttling-related switching losses by switching 70 % faster than comparable commercial valve designs.

Linear actuators, off-highway vehicle electrificat↗
DOE OSTI2022

High-Temperature Ceramic-Carbonate Dual-Phase Membrane Reactor for Pre-combustion Carbon Dioxide Capture (Final Scientific/Technical Report)

Arizona State University, in collaboration with University of South Carolina, worked on a project aimed at development of a new high temperature, high pressure CO 2 perm-selective membrane reactor for water-gas-shift reaction (WGS) with simulated gasifier syngas to produce a high concentration H 2 stream with CO 2 capture. The membrane reactor is made of a CO 2 semi-permeable ceramic-carbonate dual-phase (CCDP) membrane with high CO 2 perm-selectivity/permeance and thermal/mechanical stability for application in WGS reaction. The objectives of this project were to (1) synthesize the chemically/thermally stable tubular CCDP membranes with CO 2 permeance and selectivity (with respect to H 2 , CO or H 2 O) larger than 6.5×10-7 mol/m2·s·Pa and 500, respectively; (2) establish CCDP membrane reactor setup and study high pressure CO 2 permeation and WGS reaction with CO 2 capture using the setup; and (3) identify conditions for WGS in the CCDP membrane reactor that produce CO 2 and H 2 streams with purity of >99% and >90% respectively at CO conversion >95% and overall carbon capture >90%. The work in this project included both membrane development and membrane reactor process study. The membrane development efforts were focused on investigating a H 2 S resistant and highly oxygen-ionic conducting metal oxide material and membrane for CO 2 separation, fabrication of tubular samaria-doped-ceria/molten-carbonate CCDP membrane with high mechanical strength, and experimental and modeling study of high-pressure CO 2 permeation of the CCDP membranes. Mathematical models were developed to describe WGS in the CCDP membrane reactor without a catalyst or packed with a commercial high temperature WGS catalyst. Experiments on WGS in the CCDP membrane reactor with the commercial WGS catalyst, guided by the model analysis, were performed to identify optimum conditions for achieving the CO conversion, carbon capture, and the purity of the H 2 and CO 2 streams mentioned above. At 30 atm feed pressure, 750°C operation temperature, space velocity of 250 h-1, and with steam sweep, a single-stage CCDP membrane reactor with average CO 2 permeation flux of 0.5 cm3(STP)/min.cm2 can achieve CO 2 conversion of 95% and overall carbon capture of 94%, and produce CO 2 and H 2 streams with dry-based purity of >99% and 92% respectively. The project also included process design and techno-economic analysis (TEA) for a CCDP membrane reactor process for WGS reaction with CO 2 capture for a 550 MW coal-fired IGCC power plant, and its comparison with the conventional fixed-bed reactor system for WGS with follow-up CO 2 capture by an amine absorption process. The target performance for the reactor for WGS with CO 2 capture includes CO conversion >95%, hydrogen stream purity >90%, CO 2 stream purity >95%, and total carbon capture >90%. The CCDP membrane developed in this project can achieve the performance target, without subsequent CO 2 capture process at the optimum conditions identified in this project. The outcome of the process design and TEA analysis shows that the membrane reactor for WGS with in-situ CO 2 capture has an operating cost about 40% lower than that for the conventional fixed-bed reactor with a separate amine absorption process for CO 2 capture. However, the capital cost of the membrane reactor process is about twice that of the conventional process because of the higher cost of the CCDP membrane. Modeling analysis shows that a membrane reactor using a CCDP membrane with higher CO 2 permeance (about three times the current value) can deliver the targeted performance for WGS reaction with CO 2 capture at a much higher space velocity and lower membrane surface area to catalyst volume ratio, leading to a smaller catalyst amount and/or membrane area and hence significantly reduced membrane reactor capital costs.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Surface Roughness Effects from Additive Manufacturing in High Efficiency Gas Turbine Combustion Systems

In the past, clean combustion systems were characterized by high system development costs due to growing complexity and escalating manufacturing costs from conventional manufacturing processes. As a result, high efficiency concepts are difficult to design and more difficult to be cost-effectively manufactured. In recent years, with the introduction of additive manufacturing (AM) technologies, the rapid prototyping and mass production processes of clean combustion systems are promising to be significantly simplified with significant reduction in terms of engine manufacturing cost and engine energy cost. Compared with conventional manufacturing built parts, the AM process enabled a simpler design to be adopted for the nozzle, reducing the number of required braze and weld joints from twenty-five to just five. The resulting nozzle was 25% lighter and five times more durable and contributed to a 15% reduction in fuel burn in comparison with the previous model produced. Applying these improvements to a fleet of 5,000 turbofan engines at 150 kN thrust would result in fuel cost savings of $ \$ $6B annually (at $ \$ $5/gallon Jet-A fuel price, 700 gallon/hour fuel consumption rate, and 2,300 operational hours per year), and reduce CO2 emissions by more than 25 million tons per year. These advances support core Department of Energy (DOE) missions in energy efficiency, improving productivity, and environmental sustainability. Maximizing the benefit of these new capabilities will require high prediction capability of high speed turbulent flow with wall modeled Large Eddy Simulation (LES). GE Aviation maintains that advanced simulation technology and supercomputing is required in order to provide the appropriate boundary conditions to realize the maximum potential of AM and Ceramic Matrix Composite to reduce cooling flow, a first order penalty on the Brayton cycle. The algorithm developed using the ANSYS/Fluent software would provide the foundation for entirely new avenues of research and development with potential multi-billion dollar impact to the US economy, and significant reduction in carbon based emissions across the aerospace and power generation industries. The formulation of this iWLES (integral wall model for LES) is generic and allows to capture the changes in flow dynamics that have a significant impact on the wall bounded flow characteristics, such as swirler effective area, bulk swirl number, local pressure distribution, exit velocity profile, and turbulence kinetic energy profile. A periodic channel flow with rough flat plate is simulated using LES (Wall-Adapting Local Eddy-viscosity) model to verify the implementation of iWLES in the Fluent User Defined Function (UDF). As the flow fields are highly sensitive due to surface roughness of the wall bounded flows in the combustion systems, there is significant potential to conduct further LES studies focusing on the turbulence boundary layer interaction. Accurately capturing near wall physics will elucidate the impact of rough surfaces on combustor flow and aero-thermal interactions.

42 ENGINEERING↗
DOE OSTI2021

Simulation of Premixed and Partially Premixed Jet-in-Crossflow Flames at High Pressure

In this paper, we explore the operational map of a lean axial-staged combustor of premixed and partially premixed reacting jet-in-crossflow flames at high -pressure (5 atm). This study attempts to expand the data to relatively high pressure and could significantly aid scaling to real gas turbine engine conditions at 20–30 atm. High-speed camera, particle image velocimetry (PIV), CH* chemiluminescence, temperature, and pressure measurements were taken and processed to allow accurate reconstruction of six operating points relative to computational fluid dynamics (CFD) simulations under minimal adjustments. Variation of lean main stage (φ = 0.575 and 0.73) and rich jet (φ = 1.1, 4, and 8) equivalence ratio has been investigated for a four mm axial jet. The fully premixed flames were found to be controlled by the crossflow temperature before ignition and the crossflow oxygen content during combustion. Analysis of flame shape and position for the partially premixed operating points describes a lee stabilized as well as a more unsteady windward flame branch. Adjustment of added jet fuel and crossflow temperature along with its corresponding oxygen level is required to attain a compact flame body. Here, the risk of delaying combustion progress is significantly increased at a richer jet φ = 8 and an overshooting, spatially divided flame was attained with a main stage φ = 0.73. Control toward a compact flame body is critical to allow combustion at reasonable reaction rate.

03 NATURAL GAS↗
DOE OSTI2020

Wireless Instrumented RB Experiment Preliminary Design and Analysis

The ability to deploy new nuclear fuels for current or future reactor concepts requires carefully designed experiments to generate data to support fuel qualification. Ideally these experiments would include state of-the-art sensing to maximize the amount of in situ data that can be collected during operation. Furthermore, advanced reactor systems can take advantage of integrated in-core sensing technologies to maximize fuel utilization, reduce unnecessary conservativism in design margins, and improve operator’s understanding of limiting peaking factors. Before any novel sensing technologies can be readily adopted for nuclear applications, they must first demonstrate acceptable performance in test reactors. This report summarizes the preliminary design and analysis of the most highly instrumented irradiation experiment ever performed in the removable beryllium (RB) positions of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). The Wireless Instrumented RB Experiment 2021 (WIRE-21) will test a wide range of sensors including wireless sensors being developed by Westinghouse Electric Company (WEC) that could provide in situ measurements of peak fuel temperatures and fuel rod pressurization due to fission gas release. The ability to wirelessly transmit a signal through the fuel rod’s cladding is critical to improving fuel monitoring capabilities without requiring signal penetrations through the cladding pressure boundary, which would significantly impact fuel fabrication, handling, and operation. Other sensors that will be tested in WIRE-21 include an array of thermocouples, self-powered neutron detectors (SPNDs), and spatially distributed fiber-optic temperature sensors. More generally, WIRE-21 will establish a flexible irradiation vehicle design to allow accelerated, economical testing of advanced sensor technologies while leveraging the extremely high neutron flux that is available in HFIR. This report summarizes the mechanical design for WIRE-21, the experimental test matrix, initial neutronic and thermal design analyses, and the active monitoring and control system enhancements necessary to support testing of advanced sensor technologies. The containment for WIRE-21 is similar to previous RB irradiation vehicles but includes a few modifications, most notably the use of integrated compression seals to pass a larger number of sensor leads through the experiment’s pressure boundary. In addition to the sensor leads, inert gas lines are passed into the experiment to enable active temperature control and the ability to pneumatically actuate a bellows-driven pressure sensor. WIRE-21 is targeting temperatures (300–350°C) and neutron fluence levels (~10 22 n/cm 2 ) relevant to light water reactors (LWRs), but the flexible design of the experiment vehicle allows much higher operating temperatures (>1,100°C). Neutronic calculations determine the neutron flux conditions as well as the nuclear heating within the experiments. These results are used as inputs to detailed thermal finite element calculations, which are required to evaluate the complex, three-dimensional heat transfer that occurs within WEC’s wireless sensor enclosures. Initial results show that the temperatures of the sensors’ enclosures and the metal bellows can be operated near the temperature range of LWR coolants and cladding while simultaneously increasing the temperature of a surrogate fuel material to values in the range of 800–1200°C to simulate centerline fuel temperatures during LWR operation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2004

The Investigation Of Carbon Contamination And Sputtering Effects Of Xenon Ion Thrusters

The Electro-Physics Branch of the NASA Glenn Research Center investigates the effect of atomic oxygen, environmental durability of high performance power materials and surfaces, and low earth orbit. One of its current projects involves the analysis of ion thrusters. Ion thrusters are devices that initiate a beam of ions to a target area. The type of ion thruster that I have been working with this Summer of 2004 emits positively charged Xenon (Xe(+)) atoms through two grids, the screen grid and the accelerator grid, after it enters an ionization chamber. Insulators are used to mechanically hold and separate these two grids. A propellant isolator, an instrument that closely resembles insulators, is placed in front of the ionization chamber. Both the insulator and isolator are made with a ceramic compound and filled with insulating beads. The main difference between the two devices is that the propellant isolator allows gas to flow through, in this case, the gas is Xe(+) and the insulators do not. In order to avoid carbon deposits and other contaminating chemicals to settle on the insulators and propellant isolator, a metal shadow shield is placed around them. These shadow shields function as a protectant and can be shaped in numerous configurations. Part of my job responsibility this summer is to investigate the effectiveness of different shadow shields that are utilized on three different ion engines: the NSTAR (NASA Solar Electric Propulsion Technology Application Readiness), JIMO (Jupiter Icy Moons Orbiter), and NEXIS (Nuclear Electric Xenon Ion System). Using calculus and other mathematical tactics, I was asked to find the total flux of carbon contamination that was able to pass the protectant shadow shield. I familiarized myself with the software program, MathCad2004, to help perform some mathematical computations such as complex integration. Another method of studying the probability of contamination is by experimental simulation. After attaining the precise parameters of the actual shadow shields, I created replicas of three types of shadow shielding to be used to undergo testing. It will be placed in a machine that produces carbon atoms at a high temperature of 200 C. or beam is aimed at a targeted material. As a result of this collision, atoms and other particles are ejected out of the target surface. Another part of my internship consisted of research on sputter ejection, or the angle distribution of sputtered material. This research entailed finding the past results of sputter ejection investigation as well as creating another type of mock simulation. Other minor projects include calculating the path of Xe(+) gas through the insulating beads of the isolators and assisting my mentor in collecting data for his paper for the Joint Propulsion Conference & Exhibit to be held July 11-14,2004 in Fort Lauderdale, Florida.

Prak, Moline K.↗