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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Prediction of Breakdown in Air and Solid Dielectrics: A Complete Plasma Model from Discharge Initiation to Flashover (Final Technical Report)

A major challenge for most of the technologies of today, and the technologies of the future, is the compact and reliable design of electrical insulation systems for their electrical components. Although controlled low-temperature plasmas (LTPs) or non-thermal plasmas in air at atmospheric pressure are of interest for a wide range of technologies, the appearance of such discharges is considered highly undesirable in insulation systems because they are precursors of a breakdown or flashover, where complete insulation failure takes place. For non-thermal plasmas, often only one mechanism, or the transition from one discharge mechanism to another, has typically been studied to date. On the other hand, in the case of thermal plasma applications, the conditions following the occurrence of an electric arc or flashover have always been considered. Here, there is a big technical gap: there is no paper describing a complete plasma model simulating all discharge mechanisms and their transitions from discharge initiation to electrical arc and flashover. To address this gap, a complete plasma model for both thermal and non-thermal plasmas should be developed using a hydrodynamic approach. The project aimed to build the model. The work has the potential to address industrial applications and is of great importance to higher voltage systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Multi-scale Simulation, Calibration, and Optimization of Calcium Carbonate Precipitation in Microbial Communities

Ensuring the efficient engineering of microbially induced calcium carbonate precipitation (MICP) is crucial for a variety of environmental and civil engineering applications, such as soil stabilization and carbon sequestration. Addressing this need, we present a comprehensive multi-scale workflow that begins with the isolation of calcium carbonate-producing microbes from soil samples, followed by metagenomic sequencing and metabolic reconstruction. We then characterize microbial growth phenotypes under diverse nutrient conditions, compare observed growth with metabolic model predictions, and apply the Consistent Reproduction of Phenotype (CROP) algorithm to refine these models. Furthermore, we analyze metabolite consumption and production, and develop a consumer-resource model that is calibrated using time-series measurements of growth rates, pH levels, and calcium carbonate precipitation. The primary benefit of our approach lies in its ability to predict and control MICP outcomes, facilitated by a Bayesian methodology that incorporates priors on initial conditions and parameters. This allows us to compute posteriors by integrating experimental data, and to solve a risk optimization problem under uncertainty to identify nutrient conditions that maximize calcium carbonate production. In contrast to non-Bayesian methods, which fail to quantify uncertainty accurately, our approach provides a more reliable pathway to optimizing nutrient conditions, enhancing the likelihood of achieving desired MICP outcomes. This positions our method as a superior alternative in the quest to improve MICP through engineered microbial consortia.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Diagnostics, Prognostics, and Optimization for Lithium-Ion Battery Systems

Health management of lithium-ion battery systems presents a host of challenges due to their complex physics, large numbers of components, and a wide variety of degradation behaviors across different battery types. Dr. Paul Gasper will present on research from the Electrochemical Energy Storage Group on Lithium-ion battery diagnostics, prognostics, and optimization. Diagnostics research, including state-estimation via machine-learning from electrochemical impedance spectroscopy and DC pulses as well as continuous state-estimation via Kalman filters, will highlight the ongoing challenges for accurately measuring the state of batteries without performing time-consuming characterization tests. NLR's industry-recognized battery prognostics work, which predicts real-world battery degradation by identifying degradation rate models from accelerated aging data using statistical modeling and machine-learning, will be used to demonstrate the critical impact of battery controls, thermal management, and operating strategy on durability and lifetime. Finally, the use of prognostic models for financial or lifetime optimization will be discussed.

25 ENERGY STORAGE↗
DOE OSTI2024

Resolution requirements for high-speed droplet impact along a rigid wall

The mechanical and thermal loads that are produced on high-speed projectiles from a droplet are key in the projectile development.To accurately predict the pressure produced along the wall surface during impact, it is important to correctly model the air/water interface of the droplet. Novel modeling approaches such as the Phase-Field enable control of the (numerical) interface thickness. However, the interplay between the grid resolution (including potential adaptive mesh refinement) and the interface thickness is unclear. In this work, the resolution requirements for numerical simulations of a two-dimensional cylindrical water droplet impacting a rigid wall at Mach four are computationally investigated. Numerical simulations are performed using a second-order accurate scheme with adaptive mesh refinement and a Phase-Field interface model. The choice of numerical interface thickness and resolution parameters affects the maximum pressure and location of the maximum pressure along the wall. The overall maximum pressure does not converge even at high resolutions. The number of levels and thickness (number of cells across the interface) play a role in obtaining a well behaved solution.

Burrell, E.↗
DOE OSTI2024

Characterization and controllability of radiated power via extrinsic impurity seeding in strongly negative triangularity plasmas in DIII-D

Experiments with extrinsic impurity seeding in strongly negative triangularity shapes in DIII-D achieved radiated power fractions (relative to input power) of up to ≈85% total radiation and ≈55% core radiation in steady-operating conditions. The relationship between core and total radiation was sensitive to impurity species and input power. Attempts to reach higher radiation levels via higher impurity flows resulted in radiative collapse disruptions. Nitrogen, neon, argon, and krypton were tested. Injection was by gas puffing, usually controlled by feeding back real-time estimates for core or total radiating fractions ($P_\textrm{rad} / P_\textrm{input}$). Argon and krypton were controlled by feeding back total radiating fraction, whereas neon was controlled by feeding back the core radiating fraction, due to the lower efficiency of neon as a divertor radiator. Nitrogen flows were pre-programmed. Reasonable total $P_\textrm{rad}$ control target following was achieved with argon or krypton. Control was more challenging with the neon/core radiation configuration, which was more prone to slow response and overshooting of the control target. Poor particle removal contributed to the control challenge: neon particle inventory within the last closed flux surface was roughly constant for up to 1 s (the longest duration tested) after neon injection was halted. However, separate experiments with laser-blow off of non-recycling impurities measured a short impurity confinement time, on the scale of the energy confinement time of ∼100 ms. Modeling with the Aurora impurity transport simulation matched experimental neon density profiles with full recycling (R = 1.0) and weak pumping but predicted rapid decreases in neon inventory if pumping were increased or recycling decreased. This indicates that changes outside the confined plasma (adding a well-placed pump) would improve controllability for all highly recycling species.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Physics vs structure: A systematic benchmark of learning strategies for multi-zone building thermal dynamics

Recent advances in physics-informed and data-driven machine learning promise improved thermal models for advanced building control, yet there is limited quantitative evidence on when added physics structure and architectural complexity are beneficial. Here, this work presents a systematic benchmark of five representative system identification methods for modeling multi-zone building thermal dynamics: linear state-space models, multi-layer perceptrons, neural state-space models, neural ordinary differential equations, and physically-consistent neural networks. The methods are evaluated across multiple data regimes and zone coupling strategies. Using a high-fidelity multi-zone commercial building emulator, we examine short-term and long-term prediction accuracy, computational efficiency, and ease of development. Our results reveal critical trade-offs between prediction performance, model complexity, and physical consistency. We demonstrate that decoupled, nonlinear black-box models consistently outperform coupled physics-constrained architectures in both predictive accuracy and out-of-distribution robustness in majority of the test cases for the building type considered in the study. Our findings quantify the cost of complexity in building thermal modeling and provide concrete, actionable, scenario-based guidelines for selecting model classes for control-oriented applications.

Building thermal modeling↗
DOE OSTI2021

Factors Governing Oxygen Vacancy Formation in Oxide Perovskites

The control of oxygen vacancy (V O ) formation is critical to advancing multiple metal-oxide-perovskite-based technologies. In this work, we report the construction of a compact linear model for the neutral V O formation energy in ABO 3 perovskites that reproduces, with reasonable fidelity, Hubbard-U-corrected density functional theory calculations based on the state-of-the-art, strongly constrained and appropriately normed exchange-correlation functional. We obtain a mean absolute error of 0.45 eV for perovskites stable at 298 K, an accuracy that holds across a large, electronically diverse set of ABO 3 perovskites. Our model considers perovskites containing alkaline-earth metals (Ca, Sr, and Ba) and lanthanides (La and Ce) on the A-site and 3d transition metals (Ti, V, Cr, Mn, Fe, Co, and Ni) on the B-site in six different crystal systems (cubic, tetragonal, orthorhombic, hexagonal, rhombohedral, and monoclinic) common to perovskites. Physically intuitive metrics easily extracted from existing experimental thermochemical data or via inexpensive quantum mechanical calculations, including crystal bond dissociation energies and (solid phase) reduction potentials, are key components of the model. Beyond validation of the model against known experimental trends in materials used in solid oxide fuel cells, the model yields new candidate perovskites not contained in our training data set, such as (Bi,Y)(Fe,Co)O 3 , which we predict may have favorable thermochemical water-splitting properties. The confluence of sufficient accuracy, efficiency, and interpretability afforded by our model not only facilitates high-throughput computational screening for any application that requires the precise control of V O concentrations but also provides a clear picture of the dominant physics governing V O formation in metal-oxide perovskites.

08 HYDROGEN↗
DOE OSTI2025

Machine learning enhanced predictions of ICRF heating: Overcoming numerical limitations via data curation

In this work, we present the development of robust surrogate models for Ion Cyclotron Range of Frequencies (ICRF) and High-Harmonic Fast Wave (HHFW) heating predictions in fusion plasmas. Building upon our previous efforts to achieve real-time capable models, we identify the cause of the outliers found using TORIC in certain HHFW heating scenarios. The outliers are observed to be spurious ion Bernstein wave (IBW)-like modes caused by a wavelength control algorithm designed to address challenging scenarios with high perpendicular wavenumbers. The effect arises from the modulation in the perpendicular susceptibility, which can induce sign reversal and IBW-like propagation for scenarios featuring normalized ion Larmor radius λ i ≫ 1. We use TORIC with this algorithm disabled to generate a novel HHFW-NSTX database that is free of outliers. Surrogate models trained on this database, including Random Forest Regressor (RFR), Multi-Layer Perceptrons, and Gaussian Process Regressors (GPR), demonstrate the ability to accurately predict HHFW heating profiles, with regression scores of R 2 ∈[0.93−0.99]. Additionally we demonstrate that it is possible to generalize predictions beyond training data by the use of both RFR and GPR models, enabling the prediction of scenarios previously limited to the original model. GPR models also provide uncertainty quantification, offering insights into model confidence. This work introduces a comprehensive Verification, Validation, and Uncertainty Quantification methodology for surrogate modeling, applicable not only to ICRF heating but also to other RF heating challenges and fusion physics problems. Beyond accelerated inference, these models show effective extrapolation capabilities, providing an alternative for addressing numerical challenges.

Artificial neural networks↗
DOE OSTI2024

Dynamics of Electric Polarization and Relaxation of Ions at Humid Calcite Surfaces

Mobile ions at mineral surfaces can respond to an applied electric field, adopting a new distribution that effectively represents polarization of the electrical double layer. When the field is released, the ions relax to their equilibrium distribution. In both cases, the dynamics are characteristic of the interface. However, current models of electrokinetic phenomena are not sufficiently robust to accurately predict collective ion dynamics at structurally and chemically specific mineral–water interfaces. Here, in this study, we use electrostatic force microscopy (EFM) to investigate the dynamics of ion relaxation at hydrated calcite (104) surfaces at controlled relative humidity (RH). Electrically biased probes are used to polarize the distributions of calcium and carbonate ions that are intrinsic to this interface across a range of RH values. Polarization kinetics are tracked by monitoring the tip–sample force gradient during charging, and EFM imaging is used to characterize the spatial relaxation dynamics after the applied field is released. Electrostatic finite element modeling of the sample/probe system across length-scales from nanometers to millimeters reproduces the observed stretched exponential charging response. Together, these results allow us to estimate the ion diffusivities at the interface across a wide range of RH values. These diffusivities increase by roughly 5 orders of magnitude as the RH is increased from 5 to 90%, highlighting the critical role of adsorbed water for surface ion solvation that enables ion mobility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Modeling Savings for ENERGY STAR Smart Home Energy Management Systems

The objective of this study was to develop a repeatable and defensible methodology to analyze the energy savings for Home Energy Management Systems (HEMS) that meets the minimum requirements for certification under ENERGY STAR ® Smart Home Energy Management System (SHEMS) Version 1. Mandatory connected loads include a smart thermostat, two smart lights, and one smart power strip or smart outlet. Control strategies must include feedback to occupants through an in-home display, user programming, occupancy sensor-based controls, and responsiveness to utility signals such as demand response programs. Several occupant behavior patterns were selected to quantify the range of energy savings potential for a HEMS with this basic functionality. A literature review was conducted to establish realistic room-by-room occupancy levels and usage patterns for connected devices. A series of event-driven hourly profiles were created, followed by adjustments based on application of HEMS control strategies to thermostats, interior lighting, and plug load schedules. EnergyPlus modeling was performed using these hourly schedules in three locations (Boston, Houston, and Phoenix) to examine climate dependence of energy savings. Total site energy savings ranged from 4.3 to 27.1 MBtu/year (7%-35%), and utility bill savings ranged from $\$$123 to $\$$670/year (6%-29%). The highest predicted savings was realized by occupants that were not energy conscious prior to HEMS installation, but highly engaged with the HEMS controls once the system was installed. The smart thermostat accounted for most of the savings, followed by the smart power strip. Smart lighting did not save a significant amount of energy in our analysis, based on an assumption that efficient LEDs with no standby power would normally be installed anyway.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Radiative absorption enhancements by black carbon controlled by particle-to-particle heterogeneity in composition

Black carbon (BC) absorbs solar radiation, leading to a strong but uncertain warming effect on climate. A key challenge in modeling and quantifying BC’s radiative effect on climate is predicting enhancements in light absorption that result from internal mixing between BC and other aerosol components. Modeling and laboratory studies show that BC, when mixed with other aerosol components, absorbs more strongly than pure, uncoated BC; however, some ambient observations suggest more variable and weaker absorption enhancement. We show that the lower-than-expected enhancements in ambient measurements result from a combination of two factors. First, the often used spherical, concentric core-shell approximation generally overestimates the absorption by BC. Second, and more importantly, inadequate consideration of heterogeneity in particle-to-particle composition engenders substantial overestimation in absorption by the total particle population, with greater heterogeneity associated with larger model–measurement differences. We show that accounting for these two effects—variability in per-particle composition and deviations from the core-shell approximation—reconciles absorption enhancement predictions with laboratory and field observations and resolves the apparent discrepancy. Furthermore, our consistent model framework provides a path forward for improving predictions of BC’s radiative effect on climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

HED Hydrodynamics in the Common Modeling Framework

Within the Common Modeling Framework (CMF), the HED Hydrodynamics Project has implemented a common methodology, or "Authority", for modeling high energy density (HED) experiments by extending development of the Eulerian Applications Project code Authority, "EAPA," to include relevant physics models, customization tools and templates, and in situ and post-processing capabilities. Additionally, several models for small-scale HED experiments were successfully added to the CMF and simulations reproduce the results of preexisting, benchmarked input decks. We expect use of the CMF to improve our effectiveness in developing predictive capabilities for experiments ranging from small-scale planar single-interface, single-shock to multi-interface, multi-shock configurations and up through multi-shell inertial confinement fusion (ICF) implosions. Additionally, this will strengthen our ability to design future targeted experiments. Using the CMF infrastructure and Authorities for HED modeling has three key impacts. First, it enables a version-controlled, pedigreed and archived base model for each experiment with tools that allow easy setup, execution and analysis of simulations to assess and/or expose sensitivities to various parameters. Second, having a common base set of inputs and physics definitions helps identify systematic differences between models in the codes and experimental data to support code validation, and build confidence in our predictive capabilities. Finally, designed to work in concert with multiple programs and projects including PEM, IC, OES, V&V and DSW, the CMF supports improved collaboration and integration through shared model definitions, data, simulations and results, enhancing the workflow required to underwrite the knowledge base and capabilities ultimately required for stockpile stewardship

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Conformer-Dependent Chemistry: Experimental Product Branching of the Vinyl Alcohol + OH + O 2 Reaction

The concentration of formic acid in Earth's tropo-sphere is underestimated by detailed chemical models compared to field observations. Phototautomerization of acetaldehyde to its less stable tautomer vinyl alcohol, followed by the OH-initiated oxidation of vinyl alcohol, has been proposed as a missing source of formic acid that improves the agreement between models and field measurements. Theoretical investigations of the OH + vinyl alcohol reaction in excess O 2 conclude that OH addition to the alpha carbon of vinyl alcohol produces formaldehyde + formic acid + OH, whereas OH addition to the β site leads to glycoaldehyde + HO 2 . Furthermore, these studies predict that the conformeric structure of vinyl alcohol controls the reaction pathway, with the anti-conformer of vinyl alcohol promoting α OH addition, whereas the syn-conformer promotes β addition. However, the two theoretical studies reach different conclusions regarding which set of products dominate. We studied this reaction using time-resolved multiplexed photoionization mass spectrometry to quantify the product branching fractions. Our results, supported by a detailed kinetic model, conclude that the glycoaldehyde product channel (arising mostly from syn-vinyl alcohol) dominates over formic acid production with a 3.6:1.0 branching ratio. Additionally, this result supports the conclusion of Lei et al. that conformer-dependent hydrogen bonding at the transition state for OH-addition controls the reaction outcome. As a result, tropospheric oxidation of vinyl alcohol creates less formic acid than recently thought, increasing again the discrepancy between models and field observations of Earth's formic acid budget.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Identifying synoptic controls on boundary layer thermodynamic and cloud properties in a regional forecast model

Although most of our understanding of boundary layer cloudiness is based on idealized, subtropical, barotropic marine environments, boundary layer clouds exist across a range of conditions. In this study, we use the Naval Research Laboratory's Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) and an automated cold-front-relative analysis framework to explore the boundary layer structure associated with low clouds across a transect through the cold front of a midlatitude synoptic cyclone. The model credibly captures boundary layer structure in line with conceptual models of midlatitude cyclones and ground-based observations at Graciosa Island in the Azores. The warm sector is conditionally unstable, with clouds that are too shallow and with too little liquid water, compared to cloud property retrievals from satellite and surface-based instruments. The cold-frontal region exhibits convection associated with weak stability and ascent. Northwest of the cold front, the boundary layer is well mixed, deeper, and capped by a strong inversion maintained by large-scale subsidence. Simulated clouds in frontal and post-frontal regions are mostly too thick, with too much liquid water and too little cloud base drizzle. The post-frontal clouds are associated with grid-scale updrafts, which appear to be the model's attempt to represent mesoscale organization of cellular convection typically observed in the cold sector of midlatitude cyclones. The deep, well-mixed post-frontal boundary layers and cloudiness are maintained by strong surface fluxes, as in cold air outbreaks. Our analysis framework serves as a unique approach to model verification, and our results offer insights into differences in boundary layer cloud behavior between subtropical and synoptic cold-sector regimes.

Eissner, Jordan M. [Univ. of Kansas, Lawrence, KS ↗
DOE OSTI2023

Controlling crystal-electric field levels through symmetry-breaking uniaxial pressure in a cubic super heavy fermion

Abstract YbPtBi is one of the heavy-fermion systems with largest Sommerfeld coefficient γ and is thus classified as a ‘super’-heavy fermion material. In this work, we resolve the long-debated question about the hierarchy of relevant energy scales, such as crystal-electric field (CEF) levels, Kondo and magnetic ordering temperature, in YbPtBi. Through measurements of the a.c. elastocaloric effect and generic symmetry arguments, we identify an elastic level splitting that is unambiguously associated with the symmetry-allowed splitting of a quartet CEF level. This quartet, which we identify to be the first excited state at Δ/ k B ≈ 1.6 K above the doublet ground state at ambient pressure, is well below the proposed Kondo temperature T K ≈ 10 K. Consequently, this analysis of the energy scheme can provide support models that predict that the heavy electron mass is a result of an enhanced degeneracy of the CEF ground state, i.e., a quasi-sextet in YbPtBi. At the same time, our study shows the potential of the a.c. elastocaloric effect to control and quantify strain-induced changes of the CEF schemes, opening a different route to disentangle the CEF energy scales from other relevant energy scales in correlated quantum materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Sensitivity of cellular automata grain structure predictions for high solidification rates

Understanding as-solidified grain structure development during constrained (G 0) alloy solidification conditions is a necessary component of understanding the larger process-microstructure relationships during additive manufacturing (AM) processing. This study applies a cellular automata (CA) model, for static solidification velocities and thermal gradients on the order of those expected in AM melt pools, to investigate grain shape development across ranges of input parameters governing temperature field evolution, nucleation, and growth. Variation in nucleated grain shape from columnar to equiaxed as a function of thermal gradient and nucleation density is modeled with CA and verified against the established transition model of Hunt and Gaumann. Furthermore, while thermal conditions and nucleation density are shown to have the largest roles on microstructure development, the sensitivity of grain structure was very unevenly distributed across parameter space. In particular, it was found that microstructure is very sensitive to mean nucleation undercooling and the interfacial response function in process space regimes near grain structure transitions, but entirely controlled by a combination of thermal gradient, solidification velocity, and nucleation density away from such transitions. The understanding of grain shape sensitivity obtained through CA modeling, particularly at large thermal gradient and nucleation density, will be necessary for accurate microstructure prediction during the extreme processing conditions and large input parameter uncertainty common to AM.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Interface morphology and dislocation-mediated processes during rapid solidification of thin films

Rapid solidification experiments have, in recent years, revealed a wealth of new microstructural phenomena that suggest a strong connection between the kinetics of solidification and the crystalline structures that emerge as a result. In this work, we investigate the interplay between interface morphology and defect-mediated processes during rapid solidification conditions using a Phase Field Crystal (PFC) model, enabling us to simultaneously and efficiently explore the physics of solidification and elasto-plasticity in the formalism of a single-field theory. We predict that there are two mechanisms by which dislocations emitted directly from the solid–liquid interface induce orientation gradients as well as the formation of subgrain boundaries within a single solidifying cell. We relate these mechanisms to the morphology of the moving solid–liquid interface and identify a suitable control parameter in the PFC model with which we can go between said morphologies by effectively changing the relative strength of the capillary length and kinetic coefficients of the solid–liquid interface. Thus, we are able to provide mechanistic explanations for several microstructural features (with an emphasis on orientation gradients and subgrain boundaries) observed during the rapid solidification of pure materials. We also provide a simple explanation for the formation of “jagged” subgrain boundaries, which is consistent with our experimental observations in rapidly solidified samples of Aluminum, whose mechanisms have thus far been unknown.

Interface morphology↗
DOE OSTI2022

A Variable Pressure Multi-Pressure Rail System Design for Agricultural Applications

This paper presents a solution for reducing energy loss in the hydraulic control system of agricultural tractors and their implements. The solution is referred to as a multi-pressure rail (MPR) and provides power to the hydraulic functions following a pressure control logic, as opposed to the traditional flow control logic typical of hydraulic systems used in off-road vehicles. The proposed hydraulic control system allows for elimination of redundant flow control valves in the state-of-the-art system, which cause excessive throttling losses leading to poor overall energy efficiency. Related work on MPR technology targets construction vehicles, where the MPR solution can allow energy recovery during overrunning loads and better engine management. This paper alternatively addresses the case of agricultural applications where functions mostly operate under resistive load conditions with slow dynamics, which offers an opportunity to target throttle losses. For this purpose, the paper introduces a variable pressure control strategy to handle the instantaneous pressure at each rail. To develop both the controller and the hydraulic system architecture, a stationary test rig is conceived and used to validate a numerical simulation model of the MPR system and its control strategy. Particular focus is given to the dynamic behavior of the system during the switches of a function between different pressure rails, which needs to ensure reduced oscillations of the flow provided to each hydraulic function. Once validated, the simulation model is used to predict the energy savings of the MPR solution in an actual application: a 435 hp hydraulic tractor powering a 16-row planter, for which operating features during typical drive cycles were available to the authors. The results show up to 59% total power reduction at the pump shaft, corresponding to 89.8% system efficiency gain.

36 MATERIALS SCIENCE↗