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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Performance and economic viability assessment of a novel CO 2 adsorbent for manufacturing and integration with coal power plants

Here, this study assesses the performance and economic feasibility of a novel CO 2 adsorbent for post-combustion capture in DOE/NETL’s 650 MWnet SubC PC power plant (case B11B). Bench-scale tests showed an initial adsorption capacity of 16.3 wt%, which decreased to 12.1 wt% after 41 adsorption–desorption cycles due to induced particle aggregation by over-humidification. With a conservative adsorption capacity of 8.8 wt% and 695 adsorption–desorption cycles, an adsorbent replenishment rate of 10 tonnes/h is necessary to capture 90% of CO 2 . The breakeven sale price of the adsorbent produced at this rate is $\$$1,293/tonne, which is 40 to 80 times lower than prices for K 2 CO 3 adsorbents reported in the literature (e.g., K 2 CO 3 /TiO 2 , K 2 CO 3 /ZrO 2 ) while providing better capture performances. Sensitivity analysis reveals that increasing the plant production rate from 10 to 40 tonnes/h reduces the sale price by 8%. The study also compares the CO 2 capture cost to Cansolv, an integrated solvent-based technology. The novel adsorbent requires 2.4 GJ/tonne of CO 2 for regeneration, lower than Cansolv’s 2.7 GJ/tonne. With conservative performance estimates, the capture cost is $\$$54/tonne of CO 2 , slightly higher than Cansolv’s $\$$45/tonne. To achieve lower or comparable capture costs to Cansolv, the adsorbent should meet one of the following conditions at a commercial scale: minimum 950 cycles, 16 wt% capture capacity, 50% of the adsorbent recovery, or a reduced cost to $\$$646/tonne by upscaling the manufactury to 75 tonnes/h.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Defect Characterization Using Positron Annihilation Spectroscopy on Laser-Ablated Surfaces

In recent years, short, pulsed laser ablation has been gaining popularity for machining small-scale test geometries from bulk samples and for efficient serial sectioning. These laser-based techniques are being added to the toolbox in material science, which makes it necessary to understand the changes in the material that occur from the laser–material interaction. Positron annihilation spectroscopy is a unique, nondestructive technique to investigate small defects in materials difficult to investigate by other tools. In this work, Doppler broadening and positron lifetime annihilation spectroscopy are utilized to help quantify the damage in materials treated with short, pulsed lasers. Using a femtosecond laser on single crystal silicon, this manuscript shows that clusters of vacancy-like defects and small voids increase systematically with laser power. Lastly, the damage induced by the laser can also reach to micrometer depths.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Relaxations of the steady optimal gas flow problem for a non-Ideal gas

Natural gas ranks second in U.S. primary energy consumption. Because most production sites are remote, gas must be transported through pipeline networks equipped with compressors, valves, and other components. For both economic efficiency and system reliability, it is desirable to operate these networks optimally. The governing physics across pipeline components entails nonlinear, non-convex equality and inequality constraints, and the most general steady-flow operations problem is a Mixed-Integer Nonlinear Program (MINLP).This work focuses on one such steady-flow problem-the Optimal Gas Flow (OGF) for a natural gas pipeline network-which minimizes production cost subject to the steady-flow physics. For day-to-day operations, the ability to quickly compute a globally optimal solution and a strong lower bound for varying demand profiles is crucial. A promising strategy is to build tight relaxations of the OGF’s nonlinear constraints. However, many nonlinearities arising from non-ideal equations of state either lack relaxations or have relaxations that do not scale to realistic network sizes. We address this gap by combining recent advances in polyhedral relaxations for univariate functions to construct tight, computationally efficient relaxations of the OGF with a non-ideal equation of state. These relaxations solve within seconds on a standard laptop. In conclusion, we demonstrate their quality through extensive numerical experiments on very large-scale test networks from the literature and find that the proposed approach proves optimality in 92% of tested instances.

03 NATURAL GAS↗
DOE OSTI2025

Experimental validation of a co-simulation architecture for modeling whole-building and detailed electrical distribution performance

This article presents an experimental validation of a co-simulation architecture for simultaneously modeling whole-building energy performance and detailed building electrical distribution system performance. The co-simulation architecture consists of a whole-building energy model (EnergyPlus®) embedded within a Modelica-based building electrical distribution system library called the Building Electrical Efficiency Analysis Model (BEEAM) using the Functional Mock-up Interface standard. We validate the model using experimental data collected at a full-scale test cell within Lawrence Berkeley National Laboratory’s FLEXLAB® facility. In conclusion, we show that the co-simulation model accurately predicts the electrical, mechanical, and thermal performance of the test cell for typical loads with both an AC and a DC electrical distribution topology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Coupling Surface Flow with High-performance Subsurface Reactive Flow and Transport Code PFLOTRAN

Water exchange between the surface and subsurface is important for both water resource management and environmental protection. In this paper, we develop coupled surface and subsurface flow simulation capability in a parallel subsurface flow and reactive transport code PFLOTRAN. We sequentially couple the diffusion wave-based surface flow with the subsurface flow governedby the Richards equation in PFLOTRAN. These two flow domains are linked with a boundary condition switching method that ensures continuity of pressure and flux at the surface-subsurface interface. We verify the coupled code against other existing hydrologic models and observation data using a number of numerical experiments. The coupled hydrological model exhibits good performance in strong parallel scaling tests. The new coupled surface and subsurface simulator significantly advance community simulation capability towards improving integrated hydrologic and biogeochemical understanding of complex systems such as watersheds and river corridors. Keywords: Surface flow, Integrated hydrological modeling, Boundary condition switching, Parallel computing

Wu, Runjian↗
DOE OSTI2023

Uncertainty analysis for techno-economic and life-cycle assessment of wet waste hydrothermal liquefaction with centralized upgrading to produce fuel blendstocks

Wet waste hydrothermal liquefaction is a promising technology for producing transportation fuels with much lower greenhouse gases emissions than petroleum-based fuels. However, its techno-economic and life cycle assessment are primarily based on laboratory scale testing data, subject to considerable uncertainties, and even bias, due to knowledge gaps. Here, a preliminary uncertainty analysis of key economic measures was conducted based on the 2019 state-of-technology model for biocrude production. Building on the preliminary analysis, this work presents a comprehensive uncertainty analysis in both economic and environmental measures of the entire supply chain of wet waste hydrothermal liquefaction to fuel blendstocks including biocrude upgrading based on the 2021 state-of-technology model. The analysis includes the most recent developments in hydrothermal liquefaction and biocrude upgrading technologies and Monte Carlo simulation based on an integrated model system including an improved reactor yield model, reduced-order process model, discounted cash flow economic model and simplified life-cycle assessment model. The estimated biocrude yield ranges from 42.2% to 52.4% with a median of 47.3%. The estimated fuel yield ranges from 34.7% to 42.7% with a median of 38.7%. The estimated minimum fuel selling price ranges from $\$ $2.28/gge to $\$ $3.45/gge with a median of $\$ $2.80/gge. Relative to petroleum-derived diesel, the estimated reduction in supply chain greenhouse gas emissions ranges from 73.4% to 81.8% with a median of 77.7%. Compared to the 2019 state-of-technology analysis, a significant improvement in biocrude selectivity and economic measures and reduction in uncertainties were achieved due to the incorporation of additional continuous experimental data sets, technology development and de-risking, and improvement in model accuracy.

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

A laboratory-scale process for producing dilithium beryllium tetrafluoride (FLiBe) with dissolved uranium tetrafluoride

Flibe Energy, Incorporated (FEI)'s conceptual Lithium Fluoride Thorium Reactor (LFTR) incorporates a chemical processing facility aimed at recovering uranium and other valuable volatile radionuclides while managing harmful radionuclides from the used fuel. The fuel utilized in this reactor is a combination of dilithium beryllium tetrafluoride (Li 2 BeF 4 or FLiBe) and uranium tetrafluoride (UF 4 ), (FLiBe/U). FEI's plan involves extracting the uranium and other valuable volatile fluoride-forming radionuclides using nitrogen trifluoride (NF 3 ). To facilitate laboratory-scale testing of uranium extraction using NF 3 and address the toxicity and physical hazards associated with beryllium and beryllium fluoride (BeF 2 ), we used a two-step process to prepare the simulated fuel salt. The first step entailed thermally decomposing ammonium beryllium tetrafluoride [(NH 4 ) 2 BeF 4 ] (ABeF) through a nominal 3-step process, combined with appropriate amounts of lithium fluoride (LiF) and UF 4 , resulting in the formation of beryllium fluoride (BeF 2 ). In the second step, the mixture was repeatedly melted and frozen at the melting point of FLiBe to prepare the eutectic FLiBe with dissolved UF 4 . Although the concept appears straightforward, the production of FLiBe/U involved various challenges. These challenges included transporting the gaseous decomposition products of ABeF, hydrogen fluoride (HF) and ammonia (NH 3 ), while preventing the formation of ammonium fluoride (NH 4 F). Additionally, it was necessary to control the reaction between the higher-than-anticipated water content in the commercial ABeF with NH 3 , HF, and the condensed NH 4 F, protect UF 4 from forming an unknown black compound, select suitable structural materials to mitigate fluoride corrosion, address the risks associated with beryllium toxicity through equipment design and operational protocols, and monitor process conditions. This article provides an account of the thermal decomposition chemistry observed in the commercial ABeF, describes the FLiBe/U production apparatus, describes the experiences and process refinements developed to prepare FLiBe/U, and presents our characterizations of prepared FLiBe/U.

Ammonium beryllium fluoride thermal decomposition↗
DOE OSTI2022

Techno-economic analysis of non-aqueous hybrid redox flow batteries

Renewable energy has become indispensable to improving human life, but its growth is hampered by a lack of cost-effective energy storage systems to solve the intermittency problem. Non-aqueous hybrid redox flow batteries (NAqHRFBs), based on lithium metal anode and organic redox molecules (redoxmers), have been investigated as an attractive energy storage option because of their high cell voltages and energy densities compared to other redox flow battery candidates. However, little is known about the economic potential of NAqHRFBs, as well as the operational and materials impacts. This research establishes a techno-economic model to analyze the capital costs of NAqHRFBs with selected organic redoxmers, including 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO). Sensitivity analyses for current density, area-specific resistance, cell voltage, electrolyte composition, redoxmer price, and equivalent molecular weight indicate the key factors in controlling NAqHRFB capital cost. To make the current NAqHRFB cost-effective, the first priority is to increase the operation current density over 10 times of those used in lab-scale tests, followed by adjusting redoxmer-related characteristics to afford more cost reduction space such as decreasing the unit price by ~20 fold. The results have shed light on potential material development and system engineering directions to make NAqHRFBs viable for renewable energy storage.

25 ENERGY STORAGE↗
DOE OSTI2020

Timing and synchronization of the DUNE neutrino detector

The DUNE neutrino experiment far detector has a fiducial mass of 40 kt. The O(1 M) readout channels are distributed over the 4 x 10kt modules and need to be synchronized to O(10 ns) with a reliable, simple, affordable system. For the majority of channels a simple DC-balanced protocol is used, with clock and synchronization information encoded on the same fibre. The remaining channels use “White Rabbit” (IEEE-1588). Small scale tests show a timing jitter of <100 ps. The DUNE timing system has been successfully prototyped at the ProtoDUNE-SP detector at CERN.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Why does a phosphonium-phosphinate ionic liquid protect the contact surfaces from wear and micropitting but increase vibration when used as an additive in rolling-sliding lubrication?

A phosphonium-phosphinate ionic liquid (IL) was studied as a lubricant additive for rolling-sliding contacts. The bench-scale test was designed to simulate automotive rear axle operation during cold start, highway towing, and overload conditions. Adding such an IL (2%) into a base oil significantly reduced wear loss and rolling contact fatigue, e.g., microcracking and micropitting, but made the vibrational noise notably higher under a low (-1.5%) sliding roll ratio (SRR). Additionally, worn surface characterization revealed an interesting texture pattern with alternating smoother plateaus and rougher valleys, which is believed to cause the high vibration. No increased vibration was observed at a high (-30%) SRR, possibly because the more aggressive sliding abrasion prevented such a surface texture from forming.

36 MATERIALS SCIENCE↗
DOE OSTI2021

AENET–LAMMPS and AENET–TINKER : Interfaces for accurate and efficient molecular dynamics simulations with machine learning potentials

Machine-learning potentials (MLPs) trained on data from quantum-mechanics based first-principles methods can approach the accuracy of the reference method at a fraction of the computational cost. To facilitate efficient MLP-based molecular dynamics and Monte Carlo simulations, an integration of the MLPs with sampling software is needed. Here, we develop two interfaces that link the atomic energy network (ænet) MLP package with the popular sampling packages TINKER and LAMMPS. The three packages, ænet, TINKER, and LAMMPS, are free and open-source software that enable, in combination, accurate simulations of large and complex systems with low computational cost that scales linearly with the number of atoms. Scaling tests show that the parallel efficiency of the ænet–TINKER interface is nearly optimal but is limited to shared-memory systems. The ænet–LAMMPS interface achieves excellent parallel efficiency on highly parallel distributed memory systems and benefits from the highly optimized neighbor list implemented in LAMMPS. We demonstrate the utility of the two MLP interfaces for two relevant example applications: the investigation of diffusion phenomena in liquid water and the equilibration of nanostructured amorphous battery materials.

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

A combinatorially complete epistatic fitness landscape in an enzyme active site

Protein engineering often targets binding pockets or active sites which are enriched in epistasis—nonadditive interactions between amino acid substitutions—and where the combined effects of multiple single substitutions are difficult to predict. Few existing sequence-fitness datasets capture epistasis at large scale, especially for enzyme catalysis, limiting the development and assessment of model-guided enzyme engineering approaches. We present here a combinatorially complete, 160,000-variant fitness landscape across four residues in the active site of an enzyme. Assaying the native reaction of a thermostable β-subunit of tryptophan synthase (TrpB) in a nonnative environment yielded a landscape characterized by significant epistasis and many local optima. These effects prevent simulated directed evolution approaches from efficiently reaching the global optimum. There is nonetheless wide variability in the effectiveness of different directed evolution approaches, which together provide experimental benchmarks for computational and machine learning workflows. The most-fit TrpB variants contain a substitution that is nearly absent in natural TrpB sequences—a result that conservation-based predictions would not capture. Thus, although fitness prediction using evolutionary data can enrich in more-active variants, these approaches struggle to identify and differentiate among the most-active variants, even for this near-native function. Overall, this work presents a large-scale testing ground for model-guided enzyme engineering and suggests that efficient navigation of epistatic fitness landscapes can be improved by advances in both machine learning and physical modeling.

biocatalysis↗
DOE OSTI2020

Elemental characterization of crystalline silicotitanate following Hanford tank waste processing

To expedite vitrification of low activity waste at the Hanford Site, a Tank-Side Cesium Removal system is being evaluated. This method utilizes an inorganic ion exchange (IX) media, crystalline silicotitanate (CST), to remove 99.9% of the 137Cs from tank waste supernate. Laboratory scale testing of the ion exchange process has been conducted by Pacific Northwest National Laboratory to evaluate Cs removal with CST in supernates collected from Hanford tanks 241-AP-107 and 241-AW-102 under prototypic plant operating conditions. In an effort to understand the selectivity and partitioning of other analytes toward CST, specifically Resource Conservation and Recovery Act (RCRA) hazardous metals, selected +2 cations, and transuranic elements, a method for the complete dissolution of CST and Cs removal from the digestate was applied to the spent CST post-processing Hanford tank waste. The CST was shown to adsorb a relevant fraction of Ca, Cd, Pb, Sr, and potentially Fe by IX and/or other mechanisms. The spent CST also adsorbed actinides, including U, Pu, Np, and Am. This work discusses digestion of CST and removal of Cs from the digestate allowing effective analysis and provides insight as to what analytes may be competing for IX sites on the CST media.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Results from the FOCAL Experiment Campaign 1: Turbine Control Co-Design

This paper summarizes the scaling approach and results from the first experimental campaign of the Floating Offshore-wind and Controls Advanced Laboratory (FOCAL) Experimental Program, which is focused on developing public data sets to support the validation of numerical models for floating wind control co-design. A 1:70 Froude-scale performance-matched model of the IEA Wind 15-MW reference turbine was designed, built, and characterized on a fixed base. The National Renewable Energy Laboratory's Reference Open-Source COntroller (ROSCO) was integrated into the scale testing to examine the impact advanced turbine and generator control strategies have on turbine performance and loads, enabling validation of control strategies for floating wind design optimization.

17 WIND ENERGY↗
DOE OSTI2026

OC7 Project Phase II: Code Comparison and Experimental Validation of Hydroelastic Effects and Member-Level Loads in Floating Structures

This paper presents results from Phase II of the OC7 project, focusing on hydroelastic modeling and member-level load prediction for a flexible floating offshore structure. Numerical predictions from 11 academic and industrial partners are validated against experimental measurements obtained from a 1:70-scale test of the VolturnUS-S semisubmersible platform. A comprehensive set of verification and validation cases is examined. The results demonstrate that hydrodynamic added mass has a significant impact on predicted elastic natural frequencies. Under regular wave excitation, the numerical models reproduce platform motions and mooring line tensions with good accuracy. Member-level loads are also predicted with reasonable accuracy. Some discrepancies are observed for potential-flow models not accounting for higher-order effects associated with the instantaneous wetted surface.

17 WIND ENERGY↗
DOE OSTI2021

Interposed pulsed power system for fast separation of radioactive beams

This paper presents the novel design of an interposed pulsed power system, developed to drive a fast-switching magnet with a large multi-mH load inductance, and high field amplitude (> 1 T). This modulator can produce variable flat-top pulses from 1 to 30 ms with rise and fall times of less than 0.5 ms at a variable duty cycle of 3–91% into a heavily inductive load. The system employs a novel over-voltage topology to overcome the inherent inductance and achieve the fast rise and fall times, switching to a precision DC supply to efficiently maintain the flattop without requiring many-kV voltage. We present a power source design consideration, including the results of computer modeling as well as the first experimental results of a modulator scaled test model will also be presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

High-throughput quantification of quasistatic, dynamic and spall strength of materials across 10 orders of strain rates

Abstract The response of metals and their microstructures under extreme dynamic conditions can be markedly different from that under quasistatic conditions. Traditionally, high strain rates and shock stresses are achieved using cumbersome and expensive methods such as the Kolsky bar or large spall experiments. These methods are low throughput and do not facilitate high-fidelity microstructure–property linkages. In this work, we combine two powerful small-scale testing methods, custom nanoindentation, and laser-driven microflyer (LDMF) shock, to measure the dynamic and spall strength of metals. The nanoindentation system is configured to test samples from quasistatic to dynamic strain-rate regimes. The LDMF shock system can test samples through impact loading, triggering spall failure. The model material used for testing is magnesium alloys, which are lightweight, possess high-specific strengths, and have historically been challenging to design and strengthen due to their mechanical anisotropy. We adopt two distinct microstructures, solutionized (no precipitates) and peak-aged (with precipitates) to demonstrate interesting upticks in strain-rate sensitivity and evolution of dynamic strength. At high shock-loading rates, we unravel an interesting paradigm where the spall strength vs. strain rate of these materials converges, but the failure mechanisms are markedly different. Peak aging, considered to be a standard method to strengthen metallic alloys, causes catastrophic failure, faring much worse than solutionized alloys. Our high-throughput testing framework not only quantifies strength but also teases out unexplored failure mechanisms at extreme strain rates, providing valuable insights for the rapid design and improvement of materials for extreme environments.

Eswarappa Prameela, Suhas (ORCID:0000000334530184)↗
DOE OSTI2020

A Privacy Preserving Model-Free Optimization and Control Framework for Demand Response from Residential Thermal Loads

We consider the problem of optimizing the cost of procuring electricity for a large collection of homes managed by a load serving entity, by pre-cooling or pre-heating the thermal inertial loads in the homes to avoid procuring power during periods of peak electricity pricing. We would like to accomplish this objective in a completely privacy-preserving and model-free manner, that is, without direct access to the state variables (temperatures or power consumption) or the dynamical models (thermal characteristics) of individual homes, while guaranteeing personal comfort constraints of the consumers. We propose a two-stage optimization and control framework to address this problem. In the first stage, we use a long short-term memory (LSTM) network to predict hourly electricity prices, based on historical pricing data and weather forecasts. Given the hourly price forecast and thermal models of the homes, the problem of designing an optimal power consumption trajectory that minimizes the total electricity procurement cost for the collection of thermal loads can be formulated as a large-scale integer program (with millions of variables) due to the on-off cyclical dynamics of such loads. We provide a simple heuristic relaxation to make this large-scale optimization problem model-free and computationally tractable. In the second stage, we translate the results of this optimization problem into distributed open-loop control laws that can be implemented at individual homes without measuring or estimating their state variables, while simultaneously ensuring consumer comfort constraints. We demonstrate the performance of this approach on a large-scale test case comprising of 500 homes in the Houston area and benchmark its performance against a direct model-based optimization and control solution.

Sivaranjani, S.↗