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At least 415 records · Page 23

Sustainable network design for multi-purpose pellet processing depots under biomass supply uncertainty

This work develops a two-stage stochastic mixed-integer programming model to manage multi- purpose pellet processing depots under feedstock supply uncertainty. The proposed optimization model would help to minimize cost and to mitigate emissions from the supply chain network. We consider three alternative Biomass Processing and Densi cation Depot (BPDD) technologies; namely, conventional pellet processing, high moisture pellet processing, and ammonia ber expansion. These three technologies pre-process/pre-treat and densify different types of biomass into more highly densi ed intermediate products for different markets in order to improve movability and overall supply network performance in terms of costs and emissions. A hybrid decomposition algorithm was developed that combines sample average approximation with an enhanced Progressive Hedging (PH) algorithm to solve this challenging NP -hard problem. Some heuristics such as Rolling Horizon (RH) heuristic, variable xing technique were later applied to further enhance the PH algorithm. Mississippi and Alabama were selected as a testing ground and ArcGIS was employed to visualize and validate the modeling results. The results of the analysis reveal promising insights that could lead to recommendations to help decision makers achieve a more cost-effective environmentally-friendly supply chain network.

09 BIOMASS FUELS↗

Preface to Special Topic: Advances in Radio Frequency Physics in Fusion Plasmas

It has long been recognized that auxiliary plasma heating will be required to achieve the high temperature, high density conditions within a magnetically confined plasma in which a fusion “burn” may be sustained by copious fusion reactions. Consequently, the application of radio and microwave frequency electromagnetic waves to magnetically confined plasma, commonly referred to as RF, has been a major part of the program almost since its inception in the 1950s. These RF waves provide heating, current drive, plasma profile control, and Magnetohydrodynamics (MHD) stabilization. Fusion experiments employ electromagnetic radiation in a wide range of frequencies, from tens of MHz to hundreds of GHz. The fusion devices containing the plasma are typically tori, axisymmetric or non, in which the equilibrium magnetic fields are composed of a strong toroidal magnetic field generated by external coils, and a poloidal field created, at least in the symmetric configurations, by currents flowing in the plasma. The waves are excited in the peripheral regions of the plasma, by specially designed launching structures, and subsequently propagate into the core regions, where resonant wave-plasma interactions produce localized heating or other modification of the local equilibrium profiles. Experimental studies coupled with the development of theoretical models and advanced simulation codes over the past 40+ years have led to an unprecedented understanding of the physics of RF heating and current drive in the core of magnetic fusion devices. Nevertheless, there are serious gaps in our knowledge base that continue to have a negative impact on the success of ongoing experiments and that must be resolved as the program progresses to the next generation devices and ultimately to “demo” and “fusion power plant.” A serious gap, at least in the ion cyclotron (IC) range of frequencies and partially in the lower hybrid frequency ranges, is the difficulty in coupling large amount of power to the plasma while minimizing the interaction between the plasma and launching structures. These potentially harmful interactions between the plasma and the vessel and launching structures are challenging: (i) significant and variable loss of power in the edge regions of confined plasmas and surrounding vessel structures adversely affect the core plasma performance and lifetime of a device; (ii) the launcher design is partly “trial and error,” with the consequence that launchers may have to be reconfigured after initial tests in a given device, at an additional cost. Over the broader frequency range, another serious gap is a quantitative lack of understanding of the combined effects of nonlinear wave-plasma processes, energetic particle interactions and non-axisymmetric equilibrium effects on determining the overall efficiency of plasma equilibrium and stability profile control techniques using RF waves. This is complicated by a corresponding lack of predictive understanding of the time evolution of transport and stability processes in fusion plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Biomass yield improvement in switchgrass through genomic prediction of flowering time

The seasonal timing of the transition from vegetative to reproductive growth has a major impact on biomass accumulation in switchgrass. Late-flowering switchgrass cultivars produce greater biomass, a critical trait for sustainable bioenergy production. Genomic prediction (GP) may allow rapid selection of late-flowering individuals with reduced time and expense for field evaluations. To evaluate GP, two flowering time traits (heading date and anthesis date) were collected on 1532 genotypes from four breeding populations: Midwest, Gulf, Atlantic, and Hybrid. These were sequenced using genotype-by-sequencing (530,792 single-nucleotide polymorphisms). Predictive ability of single-trait and multi-trait models were evaluated by cross-validation, by prediction of a progeny trial (n = 122), and through prediction of yield performance in a parallel experiment (n = 52). Predictive ability was not improved by sharing information among breeding groups. Overall, multi-trait models provided an advantage during cross-validation, but a smaller advantage during progeny prediction. Within populations, GP resulted in lower per-cycle progress than previously reported field evaluations (3.1 vs. 5.0 day –1 cycle –1 ). However, GP cycles are potentially much faster than field evaluations. When directly predicting biomass yield, the Hybrid training population had a predictive ability of 0.54–0.63. This reinforces the strong linkage between biomass yields in swards and flowering time. Furthermore, these results highlight the value of GP for rapid yield improvement in switchgrass, particularly in a breeding program designed to share information between biomass yield trials and low-cost flowering time evaluations.

09 BIOMASS FUELS↗

Error Reduction Program

The details of a study to select, incorporate and evaluate the best available finite difference scheme to reduce numerical error in combustor performance evaluation codes are described. The combustor performance computer programs chosen were the two dimensional and three dimensional versions of Pratt & Whitney's TEACH code. The criteria used to select schemes required that the difference equations mirror the properties of the governing differential equation, be more accurate than the current hybrid difference scheme, be stable and economical, be compatible with TEACH codes, use only modest amounts of additional storage, and be relatively simple. The methods of assessment used in the selection process consisted of examination of the difference equation, evaluation of the properties of the coefficient matrix, Taylor series analysis, and performance on model problems. Five schemes from the literature and three schemes developed during the course of the study were evaluated. This effort resulted in the incorporation of a scheme in 3D-TEACH which is usuallly more accurate than the hybrid differencing method and never less accurate.

Syed, S. A.↗

F-16XL Hybrid Reynolds-Averaged Navier-Stokes/Large Eddy Simulation on Unstructured Grids

This study continues the Cranked Arrow Wing Aerodynamics Program, International (CAWAPI) investigation with the FUN3D and USM3D flow solvers. CAWAPI was established to study the F-16XL, because it provides a unique opportunity to fuse fight test, wind tunnel test, and simulation to understand the aerodynamic features of swept wings. The high-lift performance of the cranked-arrow wing planform is critical for recent and past supersonic transport design concepts. Simulations of the low speed high angle of attack Flight Condition 25 are compared: Detached Eddy Simulation (DES), Modi ed Delayed Detached Eddy Simulation (MDDES), and the Spalart-Allmaras (SA) RANS model. Iso- surfaces of Q criterion show the development of coherent primary and secondary vortices on the upper surface of the wing that spiral, burst, and commingle. SA produces higher pressure peaks nearer to the leading-edge of the wing than flight test measurements. Mean DES and MDDES pressures better predict the flight test measurements, especially on the outer wing section. Vorticies and vortex-vortex interaction impact unsteady surface pressures. USM3D showed many sharp tones in volume points spectra near the wing apex with low broadband noise and FUN3D showed more broadband noise with weaker tones. Spectra of the volume points near the outer wing leading-edge was primarily broadband for both codes. Without unsteady flight measurements, the flight pressure environment can not be used to validate the simulations containing tonal or broadband spectra. Mean forces and moment are very similar between FUN3D models and between USM3D models. Spectra of the unsteady forces and moment are broadband with a few sharp peaks for USM3D.

Park, Michael A.↗

Hybrid Propulsion Technology Program

Future launch systems of the United States will require improvements in booster safety, reliability, and cost. In order to increase payload capabilities, performance improvements are also desirable. The hybrid rocket motor (HRM) offers the potential for improvements in all of these areas. The designs are presented for two sizes of hybrid boosters, a large 4.57 m (180 in.) diameter booster duplicating the Advanced Solid Rocket Motor (ASRM) vacuum thrust-time profile and smaller 2.44 m (96 in.), one-quater thrust level booster. The large booster would be used in tandem, while eight small boosters would be used to achieve the same total thrust. These preliminary designs were generated as part of the NASA Hybrid Propulsion Technology Program. This program is the first phase of an eventual three-phaes program culminating in the demonstration of a large subscale engine. The initial trade and sizing studies resulted in preferred motor diameters, operating pressures, nozzle geometry, and fuel grain systems for both the large and small boosters. The data were then used for specific performance predictions in terms of payload and the definition and selection of the requirements for the major components: the oxidizer feed system, nozzle, and thrust vector system. All of the parametric studies were performed using realistic fuel regression models based upon specific experimental data.

Jensen, G. E.↗

Visualizing How the Structure of Large-Radius Jets Shapes Their Wakes

The ATLAS collaboration has introduced and implemented a strategy for selecting and analyzing large-radius jets composed of skinny $R=0.2$ subjets in heavy ion collisions at the LHC. We show how measurements of these jets teach us about the resolution length $L_{\rm res}$ of quark-gluon plasma (QGP) and can teach us how jet substructure shapes the wakes that jets excite in the QGP droplets through which they pass. We use Hybrid Model calculations to reproduce measurements of $R_{AA}$ for large-radius jets in PbPb collisions, and study their dependence on the angle between the two skinny subjets involved in the final reclustering step of an $R=1$ jet. We show how these observables can constrain the value of $L_{\rm res}$ and demonstrate that the ATLAS data rule out any picture in which an entire parton shower loses energy coherently as if it were a single entity. Determining the degree to which the QGP can resolve partons within a jet is central to the broader program of using jet quenching measurements to probe QGP. We make further use of this setup by analyzing the response of the medium to the passage of large-radius $R=2$ jets containing two skinny subjets in gamma-jet events. We introduce novel jet-shape observables that allow us to visualize the angular shape of the soft hadrons originating from the wakes that wide jets with two skinny subjets excite in a droplet of QGP, as a function of the angular separation between the subjets. We find that even when they are $\sim 0.8- 1$ radian apart, a single broad wake is produced. Only when the two subjets are even farther apart is the presence of two sub-wakes revealed. We show that the way in which jet structure shapes jet wakes can be visualized with similar clarity in experiments by using only those hadrons with low $p_T$. These observables thus offer a new and distinctive way of seeing jet wakes in heavy ion collision data.

FOS: Physical sciences↗

Further analytical study of hybrid rocket combustion

Analytical studies of the transient and steady-state combustion processes in a hybrid rocket system are discussed. The particular system chosen consists of a gaseous oxidizer flowing within a tube of solid fuel, resulting in a heterogeneous combustion. Finite rate chemical kinetics with appropriate reaction mechanisms were incorporated in the model. A temperature dependent Arrhenius type fuel surface regression rate equation was chosen for the current study. The governing mathematical equations employed for the reacting gas phase and for the solid phase are the general, two-dimensional, time-dependent conservation equations in a cylindrical coordinate system. Keeping the simplifying assumptions to a minimum, these basic equations were programmed for numerical computation, using two implicit finite-difference schemes, the Lax-Wendroff scheme for the gas phase, and, the Crank-Nicolson scheme for the solid phase.

Hung, W. S. Y.↗

Integrated aeroservoelastic analysis capability with X-29A analytical comparisons

An extension of the program STARS (a general-purpose structural analysis program) has been developed; this extension implements a complete aeroservoelastic analysis capability. Previous capabilities included finite-element modeling as well as statics, buckling, vibration, dynamic response, and flutter analyses. This paper presents a description and the formulation of STARS in its current state along with example dynamic, aeroelastic, and aeroservoelastic analyses pertaining to the X-29A aircraft. These examples include vibration analysis results as well as flutter analysis results obtained by the conventional k method and the velocity root-contour solution. Finally, selected open- and closed-loop aeroservoelastic analysis results based on a hybrid formulation are compared to illustrate, using the calculated frequency responses, the interactions of structures, aerodynamics, and flight controls.

Gupta, K. K.↗

Distributed Wind: Supporting the Clean Energy Transition

Distributed wind technologies have advanced a great deal over the last decade, developing from a very selective market to one that is poised to play a significant role in supporting a clean energy transition. Summarizing technical and modeling advances, most of them supported by program efforts undertaken by the Wind Energy Technology Office of the U.S. Department of Energy, this presentation provides an overview of the current state of distributed wind technologies and how the technology could support the wider distributed energy development. The presentation also provides an short introduction to the challenges and ongoing research to address these challenges.

distributed energy↗

Transient Modeling of Hybrid Rocket Low Frequency Instabilities

A comprehensive dynamic model of a hybrid rocket has been developed in order to understand and predict the transient behavior including instabilities. A linearized version of the transient model predicted the low-frequency chamber pressure oscillations that are commonly observed in hybrids. The source of the instabilities is based on a complex coupling of thermal transients in the solid fuel, wall heat transfer blocking due to fuel regression rate and the transients in the boundary layer that forms on the fuel surface. The oscillation frequencies predicted by the linearized theory are in very good agreement with 43 motor test results obtained from the hybrid propulsion literature. The motor test results used in the comparison cover a very wide spectrum of parameters including: 1) four separate research and development programs, 2) three different oxidizers (LOX, GOX, N2O), 3) a wide range of motor dimensions (i.e. from 5 inch diameter to 72 inch diameter) and operating conditions and 4) several fuel formulations. A simple universal scaling formula for the frequency of the primary oscillation mode is suggested.

Karabeyoglu, M. Arif↗

Lewis Research Center studies of multiple large wind turbine generators on a utility network

A NASA-Lewis program to study the anticipated performance of a wind turbine generator farm on an electric utility network is surveyed. The paper describes the approach of the Lewis Wind Energy Project Office to developing analysis capabilities in the area of wind turbine generator-utility network computer simulations. Attention is given to areas such as, the Lewis Purdue hybrid simulation, an independent stability study, DOE multiunit plant study, and the WEST simulator. Also covered are the Lewis mod-2 simulation including analog simulation of a two wind turbine system and comparison with Boeing simulation results, and gust response of a two machine model. Finally future work to be done is noted and it is concluded that the study shows little interaction between the generators and between the generators and the bus.

Gilbert, L. J.↗

Composition/Structure/Dynamics of comet and planetary satellite atmospheres

This research program addresses two cases of tenuous planetary atmospheres: comets and Io. The comet atmospheric research seeks to analyze a set of spatial profiles of CN in comet Halley taken in a 7.4-day period in April 1986; to apply a new dust coma model to various observations; and to analyze observations of the inner hydrogen coma, which can be optically thick to the resonance scattering of Lyman-alpha radiation, with the newly developed approach that combines a spherical radiative transfer model with our Monte Carlo H coma model. The Io research seeks to understand the atmospheric escape from Io with a hybrid-kinetic model for neutral gases and plasma given methods and algorithms developed for the study of neutral gas cometary atmospheres and the earth's polar wind and plasmasphere. Progress is reported on cometary Hydrogen Lyman-alpha studies; time-series analysis of cometary spatial profiles; model analysis of the dust comae of comets; and a global kinetic atmospheric model of Io.

Combi, Michael R.↗

Analysis and Optimization of Baseline Single Aisle Aircraft for Future Electrified Powertrain Flight Demonstrator Comparisons

The purpose of this study is to provide baseline single-aisle vehicles for future comparisons with NASA’s Electrified Powertrain Flight Demonstration (EPFD) turbofan-powered Vision Systems. State-of-the-art single-aisle transports with varying design capacities of 100 to 150 passengers are modeled using NASA Ames Research Center’s General Aviation Synthesis Program (GASP) as well as GASPy. GASPy is a modernized Python-based version of GASP built on the OpenMDAO framework to allow for future, efficient gradient-based optimization and coupled airframe-propulsion design. In order to meet projected NASA Aeronautics goals for 2035, advanced aircraft technologies must be incorporated into these vehicle systems. Methodology to parametrically infuse baseline aircraft models with advanced technologies simulating improvements in aerodynamics, structures, and propulsion systems is detailed, along with the results of technology sensitivity studies. Comparison of the baseline and advanced configurations will allow for future analysis of the benefits of future hybrid and fully electric aircraft concepts in the EPFD project, where fuel consumption and emissions will be modeled and assessed. This study has been conducted under the EPFD project to establish benchmark turbofan models and demonstrate System Analysis capabilities in multi-disciplinary aircraft design, analysis, and optimization for advanced turbofan concepts.

Carl J. Recine↗

A Novel Hybrid Reformer-Electrolyzer-Purifier (REP) for Distributed Production of Low-Cost, Low Greenhouse Gas Hydrogen

FuelCell Energy with support from the Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) has investigated the production of low-cost, low CO2 hydrogen using a molten carbonate fuel cell operating as an electrolyzer. We confirmed the feasibility of the technology by testing a large-scale short stack. Economic analysis was done with the assistance of the National Fuel Cell Center at the University of California, Irvine and we found the technology to be attractive, especially for distributed hydrogen. We explored the performance under various operating parameters and developed an accurate model for further analysis and development calculations. We achieved the expected results, meeting all program goals. We identified additional uses of the technology such as for CO2 capture, power storage, and power load leveling.

08 HYDROGEN↗

Data for: A hybrid biophysical-machine learning framework for diurnal surface energy flux estimation using proximal sensing

Thermal-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal datasets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for specific surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of an ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81-0.94) and H (R2 = 0.46-0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical – machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

Agricultural Sciences↗

AI Applications to Physics Experiments at Jefferson Lab

We survey how AI/ML is being deployed across Jefferson Lab's experimental and accelerator programs. In EPSCI, Hydra applies computer vision to automate real-time data-quality monitoring across all four experimental halls, replacing manual inspection of hundreds to thousands of histograms per shift. AIEC (AI Experiment Controls) uses ML to stabilize drift chamber gains and is now part of standard CEBAF production running, while AI Optimized Polarization (AIOP) targets autonomous control of polarized targets and photon beam angular alignment. In CASA, cavity fault classification models identify faulted cavities and trip types from waveform data with ~85% and ~78% agreement to labeled data, respectively, and are deployed in production; a separate effort applies LLMs and hybrid search to make the CEBAF operations logbook AI-ready. QCD-focused work includes transformer- and GAN-based generative models for particle-level event simulation, with distributed GAN training scaling studies on Polaris. Additional efforts span ML-on-FPGA for the EIC and a new Data Science Department coordinating anomaly detection, uncertainty quantification, and HPC-scalable ML lab-wide. Collectively, these projects illustrate AI's growing role in improving efficiency across JLab's nuclear physics mission.

Mei, Xinxin [Thomas Jefferson National Accelerator↗

Optimal Operation of Residential High Performance Water Heater for Reduction of Electricity Cost and Peak Demand Through Field Validation

Water heating accounts for about 18% of a typical US home’s energy use. Modern water heaters have enabled control options through APIs, offering customers the opportunity to reduce their energy cost and peak demand by dynamically adjusting settings. A water heater’s capacity to store energy using its storage tank makes it an asset for peak demand reduction and energy cost savings. For this reason, a mixed-integer linear programming model is proposed to minimize the energy cost of a high-performance water heater while also reducing the peak demand of the residential household under a time-of-use utility rate by dynamically changing the water heater’s running mode. Specifically, a multi-objective optimization model is formulated to determine the mode settings of the water heater considering hot water use, time-of-use rate, and peak demand limit of the residential household. The mode settings are associated with different dead bands of water temperature for triggering on/off action of the heat pump and heating element. A 66-gal hybrid electric high performance water heater was used for numerical simulation and practical experiments. The simulation results were well aligned with measurements of practical experiments, validating the soundness of the thermodynamic model. In addition, reductions of energy cost, enabling affordability, and reducing peak demand are demonstrated. The research team also developed a software framework with dashboards to automatically and continuously monitor and manage devices.

Liu, Guodong [ORNL] (ORCID:0000000213498608)↗