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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 OSTI2020

Dispersion of cryogenic hydrogen through high-aspect ratio nozzles

Liquid hydrogen is increasingly being used as a delivery and storage medium for stations that provide compressed gaseous hydrogen for fuel cell electric vehicles. In efforts to provide scientific justification for separation distances for liquid hydrogen infrastructure in fire codes, the dispersion characteristics of cryogenic hydrogen jets (50–64 K) from high aspect ratio nozzles have been measured at 3 and 5 bar abs stagnation pressures. These nozzles are more characteristic of unintended leaks, which would be expected to be cracks, rather than conventional round nozzles. Spontaneous Raman scattering was used to measure the concentration and temperature field along the major and minor axes. Within the field of interrogation, the axis-switching phenomena was not observed, but rather a self-similar Gaussian-profile flow regime similar to room temperature or cryogenic hydrogen releases through round nozzles. The concentration decay rate and half-widths for the planar cryogenic jets were found to be nominally equivalent to that of round nozzle cryogenic hydrogen jets indicating a similar flammable envelope. The results from these experiments will be used to validate models for cryogenic hydrogen dispersion that will be used for simulations of alternative scenarios and quantitative risk assessment.

08 HYDROGEN↗
DOE OSTI2020

Absorber Column CFD model validation against PNNL’s device-scale absorber column on the LCFS unit

Absorber column has been widely used for CO 2 capture in the coal-fired power plants. High-fidelity CFD models play an important role in absorber column design and solvents optimization, which help enhance the CO 2 capture efficiency and reduce the operation cost. This report provides a comprehensive description of the development of CFD absorber models at two different levels, the design and implementation of PNNL’s device-scale absorber column experiment, and the methodology to combine the CFD results, experiment data, and Aspen model for a better understanding of the interface area in packed column. A composite model is firstly proposed in the Discrete Element Method (DEM) packing process, which can model the complex geometry of various packing elements. This generates a realistic packing pattern and accurate packing porosity ε and specific area a p compared to the actual values for absorber column used in LCFS. Two level of CFD absorber models were developed, namely the full-size column model (FCM) to simulate the entire packed column with a focus on the wall/entrance effects, and the representative column model (RCM) to simulate a section of column with a focus on the sensitivity study of interface area. A Design of Experiment (DoE) plan was developed to guide the collection of 100 run CFD data and 12 experiment runs. The 100 CFD runs were carried out in the RCM with Pro-Pak packing and cover a wide operation range and solvent properties. Impact of influential factors on the interface area in packed column were investigated in details. The CFD interface area was then combined with the experimental data and Aspen model to infer some information of the effective contact angle in the column. The accuracy and uncertainties in the interface area and contact angle can be quantified.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Computational Analysis of the Effect of Structured Packing Design on Absorption Column Hydrodynamics for Post-Combustion Carbon Capture Applications

Solvent based post-combustion carbon capture technologies have a potential for reducing carbon emissions from fossil-fuel-fired power plants and industrial sources where CO2 emissions are inherently harder to mitigate, such as steel or cement industries. A prominent technology to achieve this is by retrofitting absorption columns to the existing infrastructure. While these systems have been among the less costly alternatives for carbon capture, they still impose a considerable energy penalty to the operation of power plants or industrial facilities. The optimization of CO2 capture rate in solvent-based absorption process is complex as it depends on several factors including CO2 solubility, solvent reaction kinetics and temperature effects on the solubility, reaction rates, surface tension, and thermophysical properties of the solvent and the flue gas. The overall heat and mass transfer also depends on the hydrodynamics, which in turn, is affected by the packing geometry. In the current work, we systematically quantify the effects the design of the structured packing has on the column hydrodynamics, by performing detailed CFD simulations for different geometrical configurations and operating conditions. We then obtain relationships between the key hydrodynamic metrics, such as liquid holdup, interfacial area, wetted area, and pressure drop to the parameters defining the packing geometries and identify new more effective packing designs for the given operating conditions.

Shah, Yash Girish↗
DOE OSTI2018

Advanced Ultrasupercritical (AUSC) Materials Thick-Walled Cycling Header Development for ComTest-AUSC (Final Report)

Alstom Power Inc., a wholly owned subsidiary of the General Electric Company (GE) recently completed “Advanced Ultrasupercritical (AUSC) Materials Thick-Walled Cycling Header Development for ComTest-AUSC” under Award No. DE-FE0026183 for the U.S. Department of Energy National Energy Technology Laboratory (DOE NETL). This project developed a design for testing of a high temperature nickel-based superalloy thick-walled header to simulate cycling and flexible plant operation in new and existing plants. The objective was to simulate the expected thermal stresses of a new AUSC plant or a retrofit header in an existing plant to improve flexible dynamic operation while maintaining component integrity and overall power plant reliability. The high performance superalloy materials that enable higher operating temperatures and pressures can support future transformational power technologies including new AUSC plants at 4250-5000 psi, 730°C/760°C or will serve as a replacement component in a repowered or retrofit USC coal powered cycling plant at 3600 psi, 600°C. These alloys can also enable supercritical CO2 cycles, nuclear power, solar power and more efficient natural gas combined cycle units as targeted by the U.S. DOE/NETL Cross-Cutting Research Technology Program Plan. Recently developed advanced nickel alloys such as Inconel 740H (740H) and Haynes 282 (H282) have been successfully tested on a pilot scale for fireside corrosion using steam loop tubing at AUSC temperatures of 760°C in actual operating coal fired boiler. These high strength materials have been demonstrated their adequacy for use in other high temperature boiler components such as superheater tubes. Thick-walled superheater outlet headers which operate at high temperatures and pressure under severe cycling condition are considered as one of the most critical component in the AUSC coal fired boiler. Over the design life of a plant, these headers are exposed to the most severe fatigue and creep damage accumulation and need to be properly designed for the expected cycling in an AUSC plant with flexible operation. These materials need to demonstrate adequate design life of 20 to 30 years for creep and fatigue conditions. The following tasks were performed: 1. A conceptual design was developed of a thick-walled component representative of typical headers with several tube connections and proper flow rates (~100,000 lbs/hr) suitable for Phase II test at 760°C operation. This was based on a process analysis of expected full scale new and component retrofit designs for AUSC; 2. A multi-physics flow and heat transfer computational fluid dynamics (CFD) analysis of the component for proper layout of the header configuration, number and geometry (size) of tubes required for bypass flow, flow rates through the tubing, and sectional pressure drops was performed. Steam to header metal heat transfer film coefficients in the header section and the tubes during the two stages (half load and full load) of the cycling operation were evaluated and used in the stress analysis; 3. Detailed analytical evaluation of the thick-walled pipe and tube connections for mechanical integrity under cycling conditions was performed. This included transient thermal stress analysis and fatigue usage estimation including the tube-to-pipe weld geometries and weld materials; 4. A layout and design of the thick-walled test component was developed and instrumentation required for a test was identified; 5. Continuum Damage Mechanics (CDM) creep prediction models were extended to 740H and H282 and validated with public data on 740H and H282 for use in creep analysis. In addition, detailed creep analyses were performed separately for the design life of the conceptual AUSC superheater outlet header using these General Electric (GE) creep constitutive models. GE was the prime contractor for the project, which was directed by Principal Investigator Robert Schrecengost and Lead Scientist Dr. B. Reddy Ganta. Other collaborative participants in this project included GE Global Research, GE Boiler Engineering, and a Technical Consultant from EPRI.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗
DOE OSTI2025

Biphasic solvents for post-combustion CO 2 capture from natural gas flue Gas

Fossil fuel fired power plants are generally expected to remain one of the most significant global sources of electricity for decades to come. Consequently, carbon management technologies are needed to reduce or eliminate ongoing emissions from these sources. Amongst the many techniques for carbon capture, aqueous amine-based absorbents (monoethanolamine, MEA, in particular) are, presently, considered the leading technology for post-combustion CO 2 point-source capture. These technologies are nevertheless limited by their high capital and regeneration energy costs. Biphasic solvents have been identified as an attractive alternative to traditional MEA based absorbents due to their potential energy savings. Thus far, however, the research on biphasic solvents has largely focused on their performance in coal flue gas while more dilute natural gas flue gas applications have received relatively little attention. Here, this work examines the performances of two novel biphasic solvent blends, diethylenetriamine (DETA) and triethylenetetramine (TETA), in CO 2 capture from a natural gas flue gas simulant. Across several regeneration tests, both solvents achieved considerable energy savings over the benchmark MEA solution. Specifically, the energy consumption per mol CO 2 recovered for the DETA-based and TETA-based solvents was 46 % and 35 % less than that of the benchmark MEA solution, respectively. Molecular dynamics simulations were also performed to gain a deeper understanding of the phase separation phenomena that occur as a consequence of CO 2 absorption. These simulations indicated that phase change was driven by the strong interaction between the absorption products and water, while the degree of separation depended on the CO 2 loading.

Biphasic solvents↗
DOE OSTI2017

Bench Scale Process for Low Cost CO 2 Capture Using a Phase-Changing Absorbent: Final Scientific/Technical Report

The objective of this project is to design and build a bench-scale process for a novel phase-changing aminosilicone-based CO 2 -capture solvent. The project will establish scalability and technical and economic feasibility of using a phase-changing CO 2 -capture absorbent for post-combustion capture of CO 2 from coal-fired power plants. The U.S. Department of Energy’s goal for Transformational Carbon Capture Technologies is the development of technologies available for demonstration by 2025 that can capture 90% of emitted CO 2 with at least 95% CO 2 purity for less than $40/tonne of CO 2 captured. In the first budget period of the project, the bench-scale phase-changing CO2 capture process was designed using data and operating experience generated under a previous project (ARPA-e project DE-AR0000084). Sizing and specification of all major unit operations was completed, including detailed process and instrumentation diagrams. The system was designed to operate over a wide range of operating conditions to allow for exploration of the effect of process variables on CO 2 capture performance. In the second budget period of the project, individual bench-scale unit operations were tested to determine the performance of each of each unit. Solids production was demonstrated in dry simulated flue gas across a wide range of absorber operating conditions, with single stage CO 2 conversion rates up to 75mol%. Desorber operation was demonstrated in batch mode, resulting in desorption performance consistent with the equilibrium isotherms for GAP-0/CO 2 reaction. Important risks associated with gas humidity impact on solids consistency and desorber temperature impact on thermal degradation were explored, and adjustments to the bench-scale process were made to address those effects. Corrosion experiments were conducted to support selection of suitable materials of construction for the major unit operations in the process. The bench scale unit operations were assembled into a continuous system to support steady state system testing. In the third budget period of the project, continuous system testing was conducted, including closed-loop operation of the absorber and desober systems. Slurries of GAP-0/GAP-0 carbamate/water mixtures produced in the absorber were pumped successfully to the desorber unit, and regenerated solvent was returned to the absorber. A techno-economic analysis, EH&S risk assessment, and solvent manufacturability study were completed.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2017

Microgrid optimized resource dispatch for public-purpose resiliency and sustainability. The Olney Town Center Microgrid Project

Communities in Atlantic coastal regions have in recent years sought to improve the resiliency of their critical infrastructure and public services, especially to protect against hurricanes and other events capable of causing widespread damage and disruption. As the backbone of any community’s critical functions, the electricity distribution system requires high resiliency in order to maintain local energy delivery services. Against this backdrop, the Project sought to develop a resilient energy microgrid control system capable of integrating distributed renewable energy resources, natural gas CHP units, energy storage, and demand-side management technologies in near-real-time optimization schemes for the community of Olney, Md. The Montgomery County Planning Board in 2005 established the Olney Town Center area as a “civic center/town commons,” in part because it serves as a key point of interaction in the community – but also because it contains numerous vital community assets. With a total peak electrical load of about 8 MW (including Montgomery General Hospital with a 2.4 MW peak), the Project area is a business and essential services area, directly serving a suburban population of more than 33,000 residents. It contains a hospital, police station, two fire stations, two schools, grocery stores, and gas stations, and the community’s water tower, among other things. Moreover, the location stands at the crossroads of two state highways that represent major regional arteries for commerce and public safety in Montgomery County. These characteristics made the Project area an appropriate setting for considering microgrid deployment. It presented a model of a typical Maryland suburban community, with geographic dispersion of vital assets over a sizeable area, and a combination of overhead distribution lines and underground cables serving those critical loads. Such a representative model helped to ensure the solutions developed and the scenarios tested would be readily applicable to other communities in the state and the region. Further, the Project’s outcomes and lessons provide insights to guide community microgrid design and development in many locations. To achieve Project objectives – including those established by the U.S. Department of Energy (DOE) National Energy Technology Laboratory – the Project team researched, developed, and tested in simulation a set of microgrid controls capable of maintaining electricity supplies for critical community loads in the event of a regional utility outage lasting many days or even weeks. Testing and analysis showed that the microgrid would be capable of maintaining electricity supply to critical loads essentially indefinitely in most outage scenarios, while also substantially improving overall reliability for microgrid customers. With targeted improvements in local utility distribution infrastructure, test analysis showed that the microgrid would be capable of reducing annual electricity outages for critical loads by 98%. Further, to help achieve environmental and efficiency policy goals established by both the State of Maryland and the federal government, the team designed the system to reduce the annual carbon footprint of served loads by 20%, and to improve system energy efficiency for those loads by at least 20%. Testing showed that, as designed, the system is capable of meeting these performance requirements, with potential for further improvements through more effective thermal energy utilization. This Final Report, comprised of four volumes and 11 annexes, presents the results of these project efforts, including feasibility assessment (section F) and guidance for decision-makers considering prospective deployment of public-purpose microgrid systems in Maryland communities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Development of a Control Platform for a Building-Scale Hybrid Solar PV-Natural Gas Microgrid

Building-scale microgrids are a type of behind-the-meter microgrids where the building operator has control of the distributed energy resources, including, in this case, a natural gas-fired microturbine in addition to solar PV and battery energy storage systems. There is a growing trend in deploying behind-the-meter microgrids due to their benefits including the resiliency of serving critical loads, especially in regions with abundant natural gas. In order to ensure distributed energy resources are dispatched optimally for the desired mode of operation, a hierarchical control platform including a centralized controller was developed and installed. The platform includes communication and control infrastructure that interface with controllers for distributed energy resources and the building automation system of a recently built energy efficient commercial building. Based on desirable outcomes under different grid and building conditions, operational modes were defined for the microgrid controller. The controller is programmed to map each mode to respective operational modes for distributed energy resources controllers. Experimental data for test runs corresponding to two operational modes confirm the communication and control infrastructure can execute hierarchical control commands. Finally, dispatch optimization for a year-long simulation of system operation is presented and the benefits of the hybrid solar PV-natural gas setup are evaluated.

Energy & Fuels↗
DOE OSTI2024

Investigation of powertrain system decarbonization using electrically assisted turbocharging and hybridization in off-road vehicles

In recent years, the causes, effects, and existential threat of a global anthropogenic climate shift have drawn significant attention and stimulated mitigation efforts from all genres of scientific, political, and industrial bodies. The greenhouse effect and the detrimental environmental impact of excess greenhouse gas (GHG) emissions, like carbon dioxide, is well studied and targeted as the primary culprit for aversive action. However, some fields exist where reducing GHG emissions is met by considerable challenges. One such field is the production and operations of off-road vehicles. Applications of these vehicles are highly diverse and are often characterized by rugged, especially transient, and power intensive duty cycles that make one-fits-all vehicle configuration solutions impractical. This research surveys existing literature to identify the modern technologies packages and challenges that face development and configuration of powertrain systems which currently navigate the regulated emissions and unique duty cycle requirements of this market space. A novel powertrain concept is proposed and evaluated with respect to the pinnacle objectives of load performance improvement, criteria pollutant reduction, and reducing the life cycle GHG intensity of its operation. A sure-fire path to vehicular GHG reduction is through improving the fuel efficiency of internal combustion engines (ICEs), an entrenched component of the off-road vehicle sector. Unfortunately, this is more easily said than done. An approach that has proven successful in this endeavor is engine downsizing and turbocharging, where a larger engine is replaced with a smaller one with added air system boosting via turbocharger to reduce frictional and pumping losses while also enabling access to additional fuel energy. However, practical realization of these potential benefits is often impeded by the transient response capability of the smaller engine across the operating space. For this reason, downsized ICE powertrains have turned to electrified forced induction systems (EFISs) for a decoupling of exhaust energy and engine speed from boost capability. Platformed on 48V hybrid technology, these systems introduce the need for more sophisticated controls around the engine gas-exchange process for the management of boost performance and exhaust gas emissions. On this account, simulation studies utilizing a GT-POWER model of a turbocharged 4.5 L engine outfit with an EFIS using an electrically driven compressor (eBooster®) are conducted to provide insight into the performance of this air handling architecture on an off-road engine. The results show that improvement in transient torque response time in sync with reduction in engine-out soot and NOx emissions are possible with an engine recalibration that leverages the transient air-fuel ratio authority of the eBooster®. Benefits are further demonstrated when duty cycle simulations of the 48V mild-hybrid engine concept are exercised, showing an acute decrease in cumulative fuel usage and soot production. Powertrain hybridization is another technological pathway achieving pronounced GHG reduction successes in modern on-road vehicle applications through integration of Li-ion battery technology. In the off-road vehicle segment, a review of available literature concludes that hybridized architectures are present but generally lack the depth of technologies that have both high specific energy and power capabilities, and thus are limited in their inclusion of Li-ion batteries for ICE assistance and enhanced energy storage capability. Therefore, building on the mild-hybrid engine results, the downsized and eBoosted engine concept was integrated into a larger high-voltage battery-hybrid series-electric powertrain system. Hybrid powertrain parameter sensitivity studies were carried out in a numerical charge-sustaining framework, providing novel insights into power flows between the battery and the engine and how their respective capabilities and operation contribute to GHG and criteria pollutant emissions of diverse duty cycles. Application of supervisory power management introduced robustness into the power sourcing and battery SOC control process and showed that optimum specification of battery properties can yield synergies between GHG emissions and battery energy capacity. Furthermore, examination of recent literature on Li-ion batteries has shown that pack manufacturing is a highly energy intensive process, thereby producing considerable quantities of GHGs that scale with energy storage capacity. Also scaling with a battery’s energy storage capacity is its investment cost. In consideration of these factors, an inclusive technoeconomic and GHG life cycle analysis is conducted. This analysis systematically compares the carbon footprint and total cost of ownership associated with the proposed hybrid powertrain concept to reference and alternative powertrain configurations, facilitating a thorough evaluation of the decarbonization effectiveness and economic viability.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2013

Ultra-High Temperature Distributed Wireless Sensors

Research was conducted towards the development of a passive wireless sensor for measurement of temperature in coal gasifiers and coal-fired boiler plants. Approaches investigated included metamaterial sensors based on guided mode resonance filters, and temperature-sensitive antennas that modulate the frequency of incident radio waves as they are re-radiated by the antenna. In the guided mode resonant filter metamaterial approach, temperature is encoded as changes in the sharpness of the filter response, which changes with temperature because the dielectric loss of the guided mode resonance filter is temperature-dependent. In the mechanically modulated antenna approach, the resonant frequency of a vibrating cantilever beam attached to the antenna changes with temperature. The vibration of the beam perturbs the electrical impedance of the antenna, so that incident radio waves are phase modulated at a frequency equal to the resonant frequency of the vibrating beam. Since the beam resonant frequency depends on temperature, a Doppler radar can be used to remotely measure the temperature of the antenna. Laboratory testing of the guided mode resonance filter failed to produce the spectral response predicted by simulations. It was concluded that the spectral response was dominated by spectral reflections of radio waves incident on the filter. Laboratory testing of the mechanically modulated antenna demonstrated that the device frequency shifted incident radio waves, and that the frequency of the re-radiated waves varied linearly with temperature. Radio wave propagation tests in the convection pass of a small research boiler plant identified a spectral window between 10 and 13 GHz for low loss propagation of radio waves in the interior of the boiler.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2013

The Application of a Statistical Downscaling Process to Derive 21 st Century River Flow Predictions Using a Global Climate Simulation

The ability of water managers to maintain adequate supplies in coming decades depends, in part, on future weather conditions, as climate change has the potential to alter river flows from their current values, possibly rendering them unable to meet demand. Reliable climate projections are therefore critical to predicting the future water supply for the United States. These projections cannot be provided solely by global climate models (GCMs), however, as their resolution is too coarse to resolve the small-scale climate changes that can affect hydrology, and hence water supply, at regional to local scales. A process is needed to ‘downscale’ the GCM results to the smaller scales and feed this into a surface hydrology model to help determine the ability of rivers to provide adequate flow to meet future needs. We apply a statistical downscaling to GCM projections of precipitation and temperature through the use of a scaling method. This technique involves the correction of the cumulative distribution functions (CDFs) of the GCM-derived temperature and precipitation results for the 20 th century, and the application of the same correction to 21 st century GCM projections. This is done for three meteorological stations located within the Coosa River basin in northern Georgia, and is used to calculate future river flow statistics for the upper Coosa River. Results are compared to the historical Coosa River flow upstream from Georgia Power Company’s Hammond coal-fired power plant and to flows calculated with the original, unscaled GCM results to determine the impact of potential changes in meteorology on future flows.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Report on High-Fidelity Dynamic Modeling of a Coal-Fired Steam Power Plant

As a result of the growth of renewables including solar and wind energy with fluctuating production, fossil fuel power plants are being required to cycle between high and low power production. This cycling is both at a greater frequency and over a wider range than in the past. In many cases, power plants are not designed for this type of cycling operation but can nonetheless endure these challenging operation requirements under the right conditions. In this project, optimal solution for enhanced flexible operations are being investigated using model based estimation and control techniques. To support the development of model-based estimator and model-based controls at GE Global Research, GE Steam Power configured a dynamic model using a reference steam plant design including the boiler, turbine, and water/steam conditioning systems as well as the controls needed for plant cycling with stability and reliability. The dynamic model was built using the APROS® software from VTT, and then calibrated to multiple load conditions from full load (100%TMCR) to partial loads (75%TMCR, 50%TMCR and 25%TMCR) based on internally developed steady state heat balance models at the unit level. These internal heat balance models are based on first principles and extensive engineering experiences from GE Steam Power as an OEM and a services provider. This topical report presents the structure of the unit level dynamic model, the tuning process, and representative simulation results from typical load cycling simulations using the dynamic model.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Extended convex hull-based distributed optimal energy flow of integrated electricity-gas systems

Integrated electricity and gas systems are constructed to facilitate the gas-fired generation, and the distributed operation of these integrated systems have received much attention due to the increased emphasis on data security and privacy between different agencies. This paper proposes an extended convex hull based method to address optimal energy flow problems for the integrated electricity and gas systems in a distributed manner. First, a multi-block electricity-gas system model is constructed by dividing the whole system into N blocks considering both physical and regional differences. This multi-block model is then convexified by replacing the nonconvex gas transmission equation with the extended convex hull-based constraints. The Jacobi-Proximal alternating direction method of multipliers algorithm is adopted to solve the convexified model and minimize its operation cost. Finally, the feasibility of the optimal solution for the convexified model is checked, and a sufficient condition is developed. If the sufficient condition is satisfied, the optimal solution for the original nonconvex problem can be recovered from that for the convexified problem. Simulation results demonstrate that the proposed method is tractable and effective in obtaining feasible optimal solutions for multi-block optimal energy flow problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Considerations for the Design of a Gas Transport System for Co-location of Microalgae Cultivation with CO 2 Sources

Co-locating microalgae cultivation facilities with sources of waste CO 2 may present opportunities for cost savings that could benefit the algal biomass industry and industries or utilities that have incentives to manage carbon emissions. However, the cost savings have not been quantified. We compare the cost of utilizing CO 2 from flue gas transported to 405-ha, base-case, open-pond microalgae facilities to the commercial purchase price of CO 2 . Sources of CO 2 include coal- and natural gas-fired power plants and ethanol, ammonia, and cement production plants in the United States. The transport of CO 2 -containing gases to the microalgae cultivation facility requires infrastructure and electricity. This engineering analysis explores the parameters that affect the infrastructure and transport distance over which emitted flue gases can be cost-effectively transported to microalgae cultivation facilities, compared to the cost of commercially purchased CO 2 (i.e., the break-even distance). Parameters that are varied include size of facility pond area, productivity, and daily duration of waste CO 2 emissions that are transported to algae. Under our assumptions and under all cases in this study, cost savings can be achieved by co-locating microalgae facilities near waste CO 2 sources. The break-even distance, which is estimated here to range from under 2 to 80 km, depends primarily on the concentration of CO 2 in flue gas, algae productivity, facility size, and pipeline system design considerations. Greater break-even distances are simulated if electricity cost is minimized, rather than if capital cost is minimized.

09 BIOMASS FUELS↗
DOE OSTI2022

Impact of particle size and particle-flow-wall coupling on pressurized oxy-combustion in the down-fired burner

Concerns over climate change have led to numerous efforts in developing low-carbon energy technologies. Pressurized oxy-combustion (POC) is a promising candidate to reduce carbon emissions in power generation. Designing an effective burner plays a vital role in developing new coal combustion technologies. Because of the high pressure, the volume fraction of coal particles at the fuel inlet of the burner of a pressurized oxy-combustor is close or even higher than the maximum limit that commercial CFD codes (e.g., ANSYS FLUENT) can handle. At this high particle volume fraction, the interactions among particles, fluid flow, and wall need to be re-evaluated. The present computational work is the first step of a systematic analysis of the particle influence, like releasing method, releasing locating, and particle size, in a pilot-scale POC combustor, developed at Washington University in St. Louis (WUSTL). In a POC process, pulverized coal is burned under elevated pressure and O2-CO2 environment. Specifically, a 15-bar, 100 kWth, POC combustor is modeled employing ANSYS FLUENT, using Reynolds-averaged Navier-Stokes (RANS) modeling. It is revealed that for this pilot-scale, pressurized burner, velocity profiles of the near-wall region in this POC facility exhibit some discrepancy against the near-wall turbulent flow velocity profile. In order to investigate the particle influence in the near-wall region, particle releasing location will be investigated. Numerical simulation results exhibit the coupling effect of turbulence flow and particles in this case. The particle size also demonstrates a great effect on particle trajectory, then further has an impact on flame stability and temperature.

Li, Lei↗
DOE OSTI2022

Combustion machine learning: Principles, progress and prospects

Progress in combustion science and engineering has led to the generation of large amounts of data from large-scale simulations, high-resolution experiments, and sensors. This corpus of data offers enormous opportunities for extracting new knowledge and insights—if harnessed effectively. Machine learning (ML) techniques have demonstrated remarkable success in data analytics, thus offering a new paradigm for data-intense analyses and scientific investigations through combustion machine learning (CombML). While data-driven methods are utilized in various combustion areas, recent advances in algorithmic developments, the accessibility of open-source software libraries, the availability of computational resources, and the abundance of data have together rendered ML techniques ubiquitous in scientific analysis and engineering. This article examines ML techniques for applications in combustion science and engineering. Starting with a review of sources of data, data-driven techniques, and concepts, we examine supervised, unsupervised, and semi-supervised ML methods. Various combustion examples are considered to illustrate and to evaluate these methods. Next, we review past and recent applications of ML approaches to problems in combustion, spanning fundamental combustion investigations, propulsion and energy-conversion systems, and fire and explosion hazards. Challenges unique to CombML are discussed and further opportunities are identified, focusing on interpretability, uncertainty quantification, robustness, consistency, creation and curation of benchmark data, and the augmentation of ML methods with prior combustion-domain knowledge.

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