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NASA NTRS2001

High Energy Electron and Gamma - Ray Detection with ATIC

The Advanced Thin Ionization Calorimeter (ATIC) balloon borne ionization calorimeter is well suited to record and identify high energy cosmic ray electrons, and at very high energies gamma-ray photons as well. We have simulated the performance of the instrument, and compare the simulations with actual high energy electron exposures at the CERN accelerator. Simulations and measurements do not compare exactly, in detail, but overall the simulations have predicted actual measured behavior quite well. ATIC has had its first 16 day balloon flight at the turn of the year over Antarctica, and first results obtained using the analysis methods derived from simulations and calibrations will be reported.

Chang, J.↗

NASA NTRS2006

Experimental Validation of a Closed Brayton Cycle System Transient Simulation

The Brayton Power Conversion Unit (BPCU) located at NASA Glenn Research Center (GRC) in Cleveland, Ohio was used to validate the results of a computational code known as Closed Cycle System Simulation (CCSS). Conversion system thermal transient behavior was the focus of this validation. The BPCU was operated at various steady state points and then subjected to transient changes involving shaft rotational speed and thermal energy input. These conditions were then duplicated in CCSS. Validation of the CCSS BPCU model provides confidence in developing future Brayton power system performance predictions, and helps to guide high power Brayton technology development.

Johnson, Paul K.↗

NASA NTRSDate not supplied

Microstructure and Mechanical Properties of Additively Manufactured Haynes 282: A Comparative Analysis between L-PBF and LP-DED Technologies

This study compares the microstructure and tensile properties of Haynes 282 fabricated using laser powder bed fusion and laser powder directed energy deposition. Both sets underwent stress-relieving, followed by hot isostatic pressing, and the standard double aging heat treatment. Tensile testing was conducted at room temperature on specimens fabricated with both technologies to evaluate and compare their tensile behaviors. Results show that the ultimate tensile and yield strengths of laser powder bed fused specimens were 18% and 57% higher, respectively than those of laser powder directed energy deposited ones, whereas the elongation to failure was similar in both. The difference in strengths is attributed to the differences in the size of ɣ' precipitates and grains, i.e., those in the LP-DED specimens being larger, whereas similar elongation to failure is attributed to the carbide debonding dominating the fracture mechanism in both batches.

Additive manufacturing↗

DOE OSTI2023

Utilizing Conjugated Imine Polymers to Stabilize Nanoparticle Silicon Anodes

Silicon anodes provide a compelling route towards delivering high-capacity lithium-ion batteries, however they are notoriously difficult to stabilize in conventional liquid electrolytes that are compatible with high performance cathodes. Furthermore, the drastic changes in volume that occur as silicon is lithiated and delithiated can lead to rapid cell failure and novel polymeric binders are known to help mitigate mechanical issues. We have recently developed a novel method to synthesize the conjugated polymer phenylmethylimine (polyPMI) using an imine metathesis reaction. We have demonstrated that this polymer can be used to stabilize silicon nanoparticles to produce a composite lithium-ion battery anode that is electrochemically stable for hundreds of lithiation and delithiation cycles with a Coulombic efficiency that is greater than 99.95% in a traditional carbonate liquid electrolyte. This work covers the structure and properties of polyPMI within the context of the unique mechanical and electrochemical requirements of nanoparticle silicon anodes. The electrochemical behavior of this polymer also offers new opportunities as an organic lithium-coordinating material that can be used to stabilize a variety of other battery electrodes. More broadly, we posit that this solution-processed, ionically conductive, and electronically conductive polymer is applicable for a variety of energy storage and conversion technologies. Finally, this work demonstrates how this novel polymer chemistry provides additional opportunities for tuning electrode architecture to target high energy full cells.

conjugated polymers↗

DOE OSTI2020

Dynamic Structure and Phase Behavior of a Block Copolymer Electrolyte under dc Polarization

There is an important consideration when designing lithium battery electrolytes for advanced applications is how the electrolyte facilitates ion transport at fast charge and discharge rates. Large current densities are accompanied by large salt concentration gradients across the electrolyte. Nanostructured composite electrolytes have been proposed to enable the use of high energy density lithium metal anodes, but many questions about the interplay between the electrolyte morphology and the salt concentration gradient that forms under dc polarization remain unanswered. To address these questions, we use an in situ small-angle X-ray scattering technique to examine the nanostructure of a polystyrene- block -poly(ethylene oxide) copolymer electrolyte under dc polarization with spatial and temporal resolution. In the quiescent state, the electrolyte exhibits a lamellar morphology. The passage of ionic current in a lithium symmetric cell leads to the formation of concurrent phases: a disordered morphology near the negative electrode, lamellae in the center of the cell, and coexisting lamellae and gyroid near the positive electrode. The most surprising result of this study was obtained after the applied electric field was turned off: a current-induced gyroid phase grows in volume for 6 h in spite of the absence of an obvious driving force. We show that this reflects the formation of localized pockets of salt-dense electrolyte, termed concentration hotspots, under dc polarization. Our methods may be applied to understand the dynamic structure of composite electrolytes at appreciable current densities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

CHARACTERIZATION OF FATIGUE BEHAVIORS OF NOTCHED 316L DED AM SPECIMENS

ASME Codification of Additive Manufacturing • Integration of AM into ASME Codes and Standards • The ASME goal is to have AM requirements in ASME Code Cases preceding the 2025 Edition. • The ASME Special Committee on AM has drafted criteria for two Code Cases for Additive Manufacturing. • AM Construction of Pressure Equipment using the Direct Energy Deposition Process with Wire Feedstock. • Includes Gas Metal Arc Welding. • Time-independent material properties. • Status - Criteria endorsed by AM Committee. • AM Construction of Pressure Equipment using the Powder Bed Fusion AM Process. • Includes Laser and Electron Beam Energy Sources. • Austenitic and Nonferrous materials. • Time-independent material properties. • Status – Approval ballot circulating to the AM Committee.

Krentz, Timothy M.↗

DOE OSTI2023

BISON Fuel Fragmentation Relocation and Dispersal (FFRD) Assessment Database for Eventual Use in Bayesian Calibration

Existing light-water reactor (LWR) fuel vendors have been interested in seeking increased discharge burnups of nuclear fuel rods for improved economics for quite a few years. With increased burnups come additional challenges that must be addressed. It has been experimentally observed that average burnups higher than the current regulatory limit of 62 MWd/kgU may undergo fuel fragmentation, relocation, and dispersal (FFRD) during a loss-of-coolant accident (LOCA). Industry must demonstrate approaches to mitigate FFRD. In an effort to support industry, the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program within the U.S. Department of Energy (DOE) has for several years invested in developing multiscale models and creating a validation/assessment database for these models to study the mechanisms driving FFRD. This report provides an update on changes made to the assessment database and new models added to BISON to support the study of fuel rod behavior during FFRD. An effort has been initiated this year to begin adding dedicated inputs to the publicly available Virtual Test Bed (VTB) repository for industry use. A section of this report details the efforts made in this area. NEAMS has recently developed new capabilities in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework’s stochastic tools module for calibration using Bayesian inference. The goal in the future is to use these capabilities to calibrate and identify weaknesses in the existing BISON models for FFRD. The report concludes with a discussion on the models most likely to benefit the most from such calibration.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Experimental assessment of antimony (Sb) in pure uranium for immobilizing fission product lanthanides

The use of fuel additives is one of the concepts to mitigate fuel cladding chemical interaction (FCCI) for metallic fuel because fission product lanthanides are expected to be immobilized by the additive. Antimony (Sb) has been discovered to be a good candidate in UZr fuel. The present study focuses on its mechanism for immobilization in pure uranium, U–4Sb alloy was fabricated to understand the Sb behavior, while U–4Sb–4Ce was fabricated to simulate the case when lanthanides are generated. Both of the as-cast and annealed samples were characterized by scanning electron microscope (SEM) and energy dispersive spectrometer (EDS). U–Sb precipitates are formed in U–4Sb alloy, while U–Sb and Ce–Sb were found in U–4Sb–4Ce alloy, thermal exposure does not change the Sb-precipitation morphologies or chemical composition. Furthermore, diffusion couple tests between those alloys and cladding materials (Fe or HT9) under 650 °C for 500 h were performed and analyzed using SEM/EDS. Diffusion couple tests demonstrate the reaction between cladding and uranium, while no reaction between Sb-precipitations and cladding materials was found.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report)

The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Poster Abstract: Leveraging Large Language Models to Reveal Interpretable Cooling Behaviors from Smart Thermostat Data

Frequent heatwaves and hot summers increasingly challenge occupant comfort, health, and energy grid stability. Addressing these challenges requires a detailed understanding of household cooling behaviors, such as thermostat adjustments and adaptive responses to extreme conditions. Traditional analyses often rely on aggregated numerical metrics that overlook subtle but important household-specific variations. In this study, we introduce a generalizable methodology that integrates large language models (LLMs) with vision capabilities to enable scalable and detailed analysis of residential thermostat data. Using Ecobee's Donate Your Data (DYD) dataset—which provides five-minute records of indoor temperatures, thermostat setpoints, and HVAC runtimes—we focus on two U.S. cities with contrasting summer climates : Austin (TX) and Phoenix (AZ). Because raw time-series data are not well suited for direct LLM analysis, we transform them into visual representations, such as daily indoor temperature trajectories and weekly runtime histograms, to better capture behavioral variations. Leveraging LLMs' visual interpretation, we extract descriptive behavioral features, including temperature preferences, time-of-day cooling orientation, anticipatory versus reactive heatwave responses, and behavioral consistency. These semantic features support unsupervised clustering to identify distinct occupant archetypes at scale, revealing differences—such as morning-centric anticipatory coolers versus households that shift toward warmer setpoints during heatwaves—that can inform demand response, resilience planning, and health-aware interventions. By converting raw numerical data into interpretable behavioral patterns, this methodology enables scalable and practical analysis of occupant behavior, supporting actionable insights for comfort, resilience, and energy management.

Nihar, Kopal↗

NASA NTRS1994

Separation of crack extension modes in composite delamination problems

This work concerns fracture mechanics modeling of composite delamination problems. In order to predict delamination resistance, an applied stress intensity factor, K, or energy release rate, G, must be compared to a mode-dependent critical value of K or G from experiment. In the interfacial fracture analysis of most applications and some tests, the mode of crack extension is not uniquely defined. It is instead a function of distance from the crack tip due to the oscillating singularity existing at the tip. In this work, a consistent method is presented of extracting crack extension modes in such cases. In particular, use of the virtual crack closure technique (VCCT) to extract modes of crack extension is studied for cases of a crack along the interface between two in-plane orthotropic materials. Modes of crack extension extracted from oscillatory analyses using VCCT are a function of the virtual crack extension length, delta. Most existing efforts to obtain delta-independent modes of crack extension involve changing the analysis in order to eliminate its oscillatory nature. One such method involves changing one or more properties of the layers to make the oscillatory exponent parameter, epsilon, equal zero. Standardized application of this method would require consistent criteria for identifying which properties can be altered without changing the physical aspects of the problem. Another method involves inserting a thin homogeneous layer (typically referred to as a resin interlayer) along the interface and placing the crack within it. The drawbacks of this method are that it requires increased modeling effort and introduces the thickness of the interlayer as an additional length parameter. The approach presented here does not attempt to alter the interfacial fracture analysis to eliminate its oscillatory behavior. Instead, the argument is made that the oscillatory behavior is non-physical and that if its effects were separated from VCCT quantities, then consistent, delta-independent modes of crack extension could be defined. Knowledge of the near-tip fields in a planar orthotropic material interfacial fracture analysis is used to determine the explicit delta dependence of VCCT parameters. Once this delta dependence is determined, energy release rates are defined with this delta dependence factored out. This modified VCCT method is applied to results from two finite element test cases. It is shown that, as predicted, delta-independent modes of crack extension result. The modified VCCT approach shows potential as a consistent method of extracting crack extension modes. It uses the same information from a finite element analysis (i.e., nodal forces and displacements) as the traditional VCCT method does. The A-independent modes extracted using the modified VCCT approach can also be used as guides to test the convergence of finite element solutions.

Beuth, Jack L.↗

DOE OSTI2023

Tunable Laser-Plasma Amplifier (Final Report)

Exploration at the laser intensity frontier has always offered new avenues for physics and reaching beyond this frontier is a grand challenge. Present-day petawatt-class lasers provide focused intensities on target of 10 22 W/cm 2 , corresponding to electric fields of 200 TV/m, while laser-plasma amplification opens a route for focused intensities well above 10 23 W/cm 2 . Intensities in this range provide the ability to test quantum electrodynamics in the unexplored low-energy, strong-field regime where signatures for new physics may arise. The behavior of matter under such extraordinary conditions is a rich and fascinating subject, not only in its own right in fundamental plasma physics, but for the many potential applications that promise to enrich the natural sciences in the future, including compact electron-beam, ion-beam particle accelerators, and ultra-bright X-ray sources. Although laser systems are now under construction internationally to access intensities of 10 23 W/cm 2 , the current technologies used appear to be fundamentally limited to these intensities. The realization of intensities beyond 10 23 W/cm 2 using parametric amplification in plasmas promises a breakthrough in high-energy density physics. Parametric amplification using Raman scattering in a plasma could provide the enabling technology for the generation of ultra-high-power laser pulses, but a more complete understanding of the nonlinear optics of plasmas is required. There is a significant gap in well-diagnosed laser-plasma instability studies of nonlinear plasma-wave phenomena, which are critical to understand for future laser-plasma devices. To achieve an efficient laser-plasma amplifier, plasma waves must be driven to large amplitude where significant energy can be rapidly transferred from the pump to the seed over the pulse duration of the seed. Simulations suggest that this nonlinear pump depletion regime can be achieved in the “pi-pulse” amplification regime. While simulations show this optimal regime with efficient amplification, it has remained elusive in experiments and there is a growing consensus within the community that thermal effects and pump beam limitations prevent laser-plasma amplifiers from progressing through the linear regime into the nonlinear pump depletion regime. Previous experiments have been significantly limited by the laser power available at the necessary wavelengths for the seed laser; therefore, the amplification is required to start in the linear regime where it is sensitive to many deleterious effects. The enabling technology (currently unique to plasma-wave amplification in the world) at the University of Rochester is the ability to provide a seed pulse with sufficient power (4 mJ/100 fs seed) to immediately drive nonlinear plasma waves into the pi-pulse regime and to tune its wavelength to optimize the efficiency of energy transfer. This in combination with the state-of-the-art OMEGA heater beams providing multiple kilojoules in a nanosecond to sufficiently heat the plasma make this system distinct from previous studies. These heater beams will provide, for the first time in Raman amplification studies, a homogeneous electron temperature high enough to prevent pump beam propagation issues that have plagued previous experiments. These systems will provide a platform for driving electron-plasma waves into the nonlinear regime where pump depletion and pulse shortening are predicted to lead to high amplification efficiencies (>30%). The Team has made significant progress through prior support from DOE Fusion Energy Sciences [DOE Office of Science Award Number DE-SC0016253 (2016-2022)]. This includes twenty-two peer-reviewed manuscripts, one patent, ten contributed talks presented at international conferences, and research that was highlighted as invited talks at fifteen international conferences. The broader impacts of this research are evident in the support of early career scientists, two Ph.D. theses, four current graduate students, a Masters Project, two undergraduate researchers, and an underrepresented minority student hired through the California Alliance for Minority Participation who now works as a Research Engineer in the group. This research met all of the funded research objectives and the highlights from primary Raman amplification thrust of this work are discussed below and form the foundation for the proposed research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Striving to translate shale physics across ten orders of magnitude: What have we learned?

Shales will play an important role in the successful transition of energy from fossil-based resources to renewables in the coming decades. Aside from being a significant source of low-carbon intensity fuels, like natural gas, they also serve as geologic seals of subsurface formations that may be used to isolate nuclear waste, sequester CO 2 , or store intermittent energy (e.g., solar hydrogen). Despite their importance, shales pose significant engineering and environmental challenges due to their nanoporous structure and extreme heterogeneity that spans at least ~10 orders of magnitude in spatial scale. Two challenges inhibit a system-level understanding: (1) the physics of fluid flow and phase behavior in shales are poorly understood due to the dominant molecular interactions between minerals and fluids under confinement, and (2) the apparent lack of scale separation that prevents a reliable (closed) description of the physics at any single scale of observation. In this review, we focus on the latter issue and discuss scale translation, which in its broadest sense is transforming data or simulations from one spatiotemporal scale to another. While effective scale translation is not exclusive to shales, but all geologic porous media, the need for it is especially acute in shales given their high degree of heterogeneity. Classical theories like homogenization, while indispensable, fail when scales are not separated. Other methods, like numerical upscaling, scale-translate in only one direction: small to large, but not the reverse, called downscaling. However, the confluence of advances in three areas are bringing challenging problems such as shales within reach: increased computational power and scalable algorithms; high-resolution imaging and multi-modal data acquisition; and machine learning to process massive amounts of data. While these advances equip geoscientists with a wide array of experimental and computational tools, no individual tool can probe the entire gamut of heterogeneity in shales. Their effective use, therefore, requires an ability to bridge between various data types obtained at different scales. The aim of this review is to present a coherent account of computational and experimental methods that may be used to achieve just that, i.e., to perform scale translation. We provide a broader definition of scale translation, one that transcends classical homogenization and upscaling methods, but is consistent with them and accommodates notions like downscaling and data translation. After a brief introduction to homogenization, we review hybrid methods, numerical upscaling and its recent extensions, multiscale computing, high-resolution imaging, and machine learning. We place particular emphasis on multiscale computing and propose an algorithmic framework to bridge between the pore (micro) and Darcy (macro) scales. Throughout the paper, we draw comparisons between the various methods and highlight their (often hidden) similarities, differences, benefits, and pitfalls. We finally conclude with two case studies on shales that exemplify some of the methods presented.

58 GEOSCIENCES↗

DOE OSTI2022

Improving bamboo’s fuel and storage properties with a net energy export through torrefaction paired with catalytic oxidation

Using torrefied char, or biocoal, as solid fuel provides an opportunity to introduce a sustainable feedstock into the energy market. The goals of this study were to investigate how torrefaction improves the energy content and the grindability of a Malaysian bamboo along with understanding the potential for integrated energy recovery from torrefaction gases. The feedstock was torrefied at 250–290 °C for 1 h and the combustion characteristics and grindability of the solid products along with the composition of torrefied gas species were measured. The results showed a beneficial increase in elemental carbon increased from 47 to 63 wt% at 290 °C torrefaction, reflecting an increase in higher heating value from 17.8 to 25.6 MJ/kg. The combustion behavior of all the products appeared to show three distinct combustion zones; however, torrefaction severity leading to higher combustion temperature and time as the fixed carbon augmented with the increase of torrefaction temperature. This increase in severity also lead to more friable and grindable material, and the 290 °C condition required a factor of 2.7 less hold-up time in the mill compared to the raw bamboo, and a factor of 8.5 less energy (938 and 111 kWh/tonne respectively). Through analysis of the gas and volatile formation, a case study showed that catalytic oxidation can convert nearly 100% of the embodied chemical energy into usable thermal energy. These experimental findings were scaled to a 100,000 tonne/y capacity torrefaction plant and in the moderate case of 270 °C operating temperature, the plant has 1.25 GJ/tonne excess energy beyond what the process needs.

09 BIOMASS FUELS↗

DOE OSTI2025

Understanding Redox Organic Behavior in Deep Eutectic Solvents: Considerations for Molecular Design

Electrolytes based on deep eutectic solvents (DESs) coupled with redox active organic molecules have shown potential as a versatile and energy dense electrochemical energy storage system. However, progress in these systems has been held back by a lack of understanding of the irregular behavior displayed when redox active organic molecules are transitioned from other solvent systems. In this work, the hydrogen bonding characteristics of a series of redox organic molecules were investigated through infrared spectroscopy and molecular modeling. New understanding of these interactions was then used to explain their electrochemical behavior in a DES electrolyte. A model was used to predict the behavior of new derivatives towards the design of an optimized redox organic-DES system. Hydrogen bonding between the redox molecules and the solvent was found to significantly shift the potential of a redox reaction more positive when a hydrogen bond forms at the redox active site. It was predicted that functionalizing a molecule with electron withdrawing groups to lower the electron density of the redox active functional group lowers the strength of the hydrogen bond and thus alleviates the undesirable potential shift. This hypothesis was demonstrated by the addition of nitro groups to fluorenones.

25 ENERGY STORAGE↗

DOE OSTI2024

Relating Solvent Parameters to Electrochemical Properties to Predict the Electrochemical Performance of Vanadium Acetylacetonate for Non-Aqueous Redox Flow Batteries

Non-aqueous redox flow batteries have shown promise for applications in grid energy storage. Increasing the efficiency of these batteries by developing the electrolyte chemistries is needed. Herein, we investigate the correlation between solvent properties and the electrochemical parameters of vanadium acetylacetonate V(acac) 3 . Using cyclic voltammetry (CV) and rotating disk electrode experiments (RDE), we show that trends in the performance of the V(acac) 3 kinetics are directly related to solvent properties. In this study, we found strong relationships between the solvents polarity, viscosity, and donor number with the electrochemical behavior of V(acac) 3 in terms of the electrochemical working widow, electron kinetics and stability towards cycling. Based on these finding, we also demonstrate how solvent selection can be improved with limited a priori knowledge.

25 ENERGY STORAGE↗

DOE OSTI2025

Rheological Properties of Enzymatically Hydrolyzed Corn Stover Pretreated via Deacetylation and Mechanical Refining

Lignocellulosic biomass is a feedstock for fuels and chemicals that does not compete with food resources and has less contaminants than refuse-derived biomass feedstocks. To convert lignocellulosics to biofuels or value-added products, multiple processing steps are typically necessary. One method of producing biofuels from lignocellulosic biomass utilizes a deacetylation and mechanical refining pretreatment and an enzymatic hydrolysis reaction to produce fermentable sugars from cellulose and hemicellulose. The rheological properties of biomass, such as yield stress and plastic viscosity, change during enzymatic hydrolysis and alter the energy requirements for pumping and mixing, an important consideration for the design of processing equipment. The dynamic changes in rheological properties that occur in a corn stover feedstock undergoing enzymatic hydrolysis are characterized in this work, and the influence on pressure losses in piping systems is estimated. Two rheometer geometries were fabricated with stereolithography 3D printing to reduce wall slip and sample ejection. The slurries have complex rheological behaviors that include shear-thinning behavior. Shear stress ramps were performed on samples at 20 and 50 degrees C using the custom geometries, and the Herschel-Bulkley model was fit to the data. The dynamic nature of the rheological properties is correlated with changes in the average fiber length at various extents of reaction, and the influence of solids concentration on the observed rheology and piping pressure losses is discussed.

09 BIOMASS FUELS↗

DOE OSTI2020

A large-scale, agent-based simulation of metropolitan freight movements with passenger and freight market interactions

This study summarizes the first stage in the implementation of an agent-based freight modeling system that has a global representation of agents and detailed modeling of a large-scale transportation network. The model is used to evaluate the transportation and energy impacts of goods movement across urban and national scales. The framework is implemented within POLARIS, a C++-based Planning and Operations Language for Agent-based Regional Integrated Simulation, which consists of an activity-based modeling (ABM) and dynamic traffic assignment (DTA) system that has robust features for passenger travel. This platform provides a tool to model interactions among consumers, producers, and the transportation system. The main objective of this initial implementation is to implement a freight model within POLARIS following an agent-based paradigm with behavioral and simulation methods. This paper presents the initial framework and illustrates the application of the model. Building upon earlier works, a parcel location assignment algorithm for business establishments in the population is documented, along with a method for estimating establishment production and consumption volumes. In addition to population generation, other features of the model include push-pull supply chains, multimodal path choice, choice of transportation logistics node, and dynamic traffic assignment. A module with e-commerce supply and demand was also developed to analyze the effects of e-commerce delivery on last-mile energy use and congestion.

agent-based freight↗