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At least 577 records · Page 32

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DOE OSTI2020

Numerical study of the effect of propped surface area and fracture conductivity on shale gas production: Application for multi-size proppant pumping schedule design

Hydraulic fracturing is a technique extensively used in the oil and gas industry, where water, proppant (sand) and additives are injected into unconventional reservoirs to enhance the recovery of shale hydrocarbon. Although some previous studies have developed pumping schedules that maximize gas production for a single-size proppant, there are very few studies that consider the effect of varying proppant diameters across pumping stages on shale gas production. Motivated by this, we carried out an extensive sensitivity analysis to determine the effect of different proppant diameters on the average fracture conductivity (FC), average propped surface area (PSA) and cumulative shale gas production volume. We found out that the cumulative shale gas production volume depends on both the average PSA and average FC. We also found out that small-diameter proppant resulted in higher average PSA and lower average FC, whereas large-diameter proppant resulted in lower average PSA and higher average FC. Hence, we designed a multi-size proppant pumping schedule considering both of these parameters into account for simultaneously propagating multiple fractures to maximize shale gas production from unconventional reservoirs. Since the size of injected proppant particles determines the average PSA and average FC for the propped hydraulic fractures, we developed a novel framework called Sequentially Interlinked Modeling Structure (SIMS) to predict the average PSA, average FC and cumulative shale gas production volume at the end of 10 years for a given pumping schedule. Then, we used this SIMS framework to obtain a multi-size proppant pumping schedule that maximizes shale gas production. In closing, we demonstrated that the obtained pumping schedule gives a cumulative shale gas production volume greater than the values obtained from the existing pumping schedules.

03 NATURAL GAS↗

DOE OSTI2020

A crisis for the verification and validation of turbulence simulations

Three algorithms have been proposed for solution of the Rayleigh–Taylor turbulent mixing problem. They are based upon three different physical principles governing the Euler equations for fluid flow. The principles serve to select the physically relevant solution from among many nonunique solutions. The admissibility principle is in dispute. The three different algorithms, expressing the three physical admissibility principles can be formulated in terms of the three energy dissipation rates or the entropy production rates, as selected by the size of the sub grid scale coefficients. These have maximal values or less than maximal values. The resulting solutions are markedly different. We find strong validation evidence that supports the maximum rate principle, based on a review of prior results and on new results presented here. We review experimental data used for validation and sufficient to discriminate among the three. We present a new analysis of this data. We show that the hypothesized long wave length perturbations in the initial conditions are not significant, so that validation can be based on this data in a straight forward manner. One of the algorithms is labeled direct numerical simulation, but is not, and as a consequence, the two algorithms with less than maximal SGS coefficients are variants of one another. Finally recommendations for the numerical modeling of the deflagration to detonation transition in type Ia supernova are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Robust cooperative control strategy for a platoon of connected and autonomous vehicles against sensor errors and control errors simultaneously in a real-world driving environment

In a real-world driving environment, a platoon of connected and autonomous vehicles (CAVs) is subject to many internal and external disturbances, resulting in uncertain vehicle dynamics. In general, the disturbances can be categorized into two types: disturbances due to vehicle sensor errors (e.g., GPS error) and disturbances due to vehicle control errors (e.g., actuator delay). In the literature, many control strategies have been proposed to improve the robustness of the CAV platoon against uncertain vehicle dynamics induced by these disturbances. However, most of these strategies only consider one type of disturbance and cannot tackle both types of disturbances simultaneously. Furthermore, they are designed to maximize the benefits of each vehicle in the platoon independently, which can deteriorate the performance of the platoon. Here, to address these problems, this study proposes a robust cooperative control (RCC) strategy to maneuver the vehicles in the platoon cooperatively to counteract the impacts of both types of disturbances. The RCC strategy is developed based on a minimax problem, where the maximization subproblem seeks to find the worst inputs for the uncertainty terms in the vehicle dynamics equation to minimize the platoon performance, while the minimization subproblem seeks to find the optimal control decisions for all subsequent vehicles to maximize the platoon performance in the worst case. To solve the minimax problem, this study proposes a globally convergent solution algorithm. It can solve the minimax problem very efficiently to enable real time deployment of the RCC strategy. Numerical application indicates that compared to the existing methods, the RCC strategy can dramatically improve the robustness of the CAV platoon against the uncertain vehicle dynamics induced by both vehicle state detection errors and vehicle control errors. Therefore, it can maneuver the CAV platoon safely and efficiently in a real-world driving environment.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Development of heavy-duty vehicle representative driving cycles via decision tree regression

Previously, researchers who developed representative driving cycles mainly focused on light-duty vehicles and only considered vehicle speed and related derivations. In this paper, we propose a novel approach to develop representative cycles for heavy-duty vehicles. By implementing decision tree regression (DTR) to the Fleet DNA on-road vehicle data, a broader set of metrics, such as engine power and fuel consumption, can be used for more robust cycle development. Additionally, the influence of each metric on the regression target is also accounted for by a weighted number derived through the DTR to enhance the representativenss of the developed cycle. As case studies, we applied the proposed method to five heavy-duty vocations (drayage, long haul, regional haul, local delivery, and transit bus) and derived the most representative cycle, as well as four extreme cycles (maximal energy consumption, maximal power-weighted work, maximal fraction of high speed, and minimal fuel economy) to advance the related alternative powertrain design.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Controlling circuitry underlies the growth optimization of Saccharomyces cerevisiae

Microbial growth emerges from coordinated synthesis of various cellular components from limited resources. In Saccharomyces cerevisiae, cyclic AMP (cAMP)-mediated signaling is shown to orchestrate cellular metabolism; however, it remains unclear quantitatively how the controlling circuit drives resource partition and subsequently shapes biomass growth. Here we combined experiment with mathematical modeling to dissect the signaling-mediated growth optimization of S. cerevisiae. We showed that, through cAMP-mediated control, the organism achieves maximal or nearly maximal steady-state growth during the utilization of multiple tested substrates as well as under perturbations impairing glucose uptake. However, the optimal cAMP concentration varies across cases, suggesting that different modes of resource allocation are adopted for varied conditions. Under settings with nutrient alterations, S. cerevisiae tunes its cAMP level to dynamically reprogram itself to realize rapid adaptation. Moreover, to achieve growth maximization, cells employ additional regulatory systems such as the GCN2-mediated amino acid control. This study establishes a systematic understanding of global resource allocation in S. cerevisiae, providing insights into quantitative yeast physiology as well as metabolic strain engineering for biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Optimizing multi-modal, non-axisymmetric plasma response metrics with additional coil rows on DIII-D

The expansion of the DIII-D tokamak operational space via the addition of new non-axisymmetric coil rows is investigated using the linear MHD plasma response code MARS-F. The plasma response to magnetic perturbations imposed by five distinct low- and high-field side coil geometries is modeled for toroidal mode numbers up to n = 6. A set of linear (~δB^2: resonant, kink mode amplitude) and quadratic (~δB: core and edge integrated NTV torque) plasma metrics are defined and compared directly for the various coil geometries. Coil size is also scanned as a secondary optimization variable. An in-vessel coil located at the low-field side midplane is identified as the most efficient plasma response actuator across all metrics and toroidal mode numbers. The multi-row combination of this new midplane (M) coil with the existing DIII-D non-axisymmetric coil set is considered in numerical optimization studies to quantify the impact of this new coil on modeled plasma response metrics. The addition of the M coil is shown to significantly increase the actuator efficiency in maximizing individual plasma response metrics as well as maximizing multi-modal ratios of response metrics, e.g. maximizing resonant modes or edge NTV torque while minimizing kink modes or core NTV torque. The ex-vessel midplane (C) coil is also observed to have an outsize effect on multi-modal optimization due to its uniquely narrow poloidal spectra, and the expansion of optimization space due to the combined use of the two existing in-vessel coil rows with both the M and C coils is notably larger than either coil's individual contribution even though both share similar poloidal locations. This four-row system is expected to greatly extend abilities to understand and optimize the control of transients and rotation on the DIII-D tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Equidistant optimization of elliptical superconducting rf standing wave cavities

A record accelerating rate was achieved earlier in standing wave (SW) SRF cavities when their shape was optimized for a lower peak surface magnetic field sacrificing the peak surface electric field. In view of new materials with higher limiting magnetic fields, expected for SRF cavities, in the first line of the Nb 3 Sn, the approach to optimization of cavity shape should be revised. A method of equidistant optimization, offered earlier for traveling wave (TW) cavities is applied to SW cavities. It is shown here that without limitation by magnetic field, the maximal accelerating rate is defined not only by limitations of the electric field but to a significant degree by the cavity shape. For example, for a cavity with the aperture radius of $R$ $a$ = 35 mm, the minimal ratio of the peak surface electric field to the accelerating rate is about $E$ pk / $E$ acc = 1.54. So, with the maximal surface field experimentally achieved $E$ pk ~ 125 MV / m, the maximal achievable accelerating rate is about 80 MeV / m even if there are no restrictions by the magnetic field. Optimized cavity shapes with and without limitations by a magnetic field are presented. Another opportunity—optimization for a low magnetic field, is opening for the same material, Nb 3 Sn, with the purpose of having a high-quality factor and increased accelerating rate that can be used for industrial linacs with cryocooler-based cooling scheme.

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Optimizing thermodynamic trajectories using evolutionary and gradient-based reinforcement learning

Here using a model heat engine, we show that neural-network-based reinforcement learning can identify thermodynamic trajectories of maximal efficiency. We consider both gradient and gradient-free reinforcement learning. We use an evolutionary learning algorithm to evolve a population of neural networks, subject to a directive to maximize the efficiency of a trajectory composed of a set of elementary thermodynamic processes; the resulting networks learn to carry out the maximally efficient Carnot, Stirling, or Otto cycles. When given an additional irreversible process, this evolutionary scheme learns a previously unknown thermodynamic cycle. Gradient-based reinforcement learning is able to learn the Stirling cycle, whereas an evolutionary approach achieves the optimal Carnot cycle. Our results show how the reinforcement learning strategies developed for game playing can be applied to solve physical problems conditioned upon path-extensive order parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Entanglement as a Probe of Hadronization

Recently, it was discovered that the proton structure at high energies exhibits maximal entanglement. This leads to a simple relation between the proton’s parton distributions and the entropy of hadrons produced in high-energy inelastic interactions, which has been experimentally confirmed. In this Letter, we extend this approach to the production of jets. Here, the maximal entanglement predicts a relation between the jet fragmentation function and the entropy of hadrons produced in jet fragmentation. We test this relation using the ATLAS Collaboration data on jet production at the Large Hadron Collider, and find a good agreement between the prediction based on maximal entanglement within the jet and the data. This study represents the first use of a quantum entanglement framework in an experimental study of the hadronization process, offering a new perspective on the transition from perturbative to nonperturbative QCD. Our results open the door to a more comprehensive understanding of the quantum nature of hadronization.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Hierarchy of multipartite correlations based on concentratable entanglement

Multipartite entanglement is one of the hallmarks of quantum mechanics and is central to quantum information processing. In this work we show that concentratable entanglement (CE), an operationally motivated entanglement measure, induces a hierarchy upon pure states from which different entanglement structures can be experimentally certified. In particular, we find that nearly all genuine multipartite entangled states can be verified through the CE. Interestingly, GHZ states prove to be far from maximally entangled according to this measure. Instead we find the exact maximal value and corresponding states for up to 18 qubits and show that these correspond to extremal quantum error correcting codes. The latter allows us to unravel a deep connection between CE and coding theory. Finally, our results also offer an alternative proof, on up to 31 qubits, that absolutely maximally entangled states do not exist. Published by the American Physical Society 2024

Schatzki, Louis (ORCID:0000000217129148)↗

DOE OSTI2021

A Non-cooperative Game-based Approach to Distributed Beam Scheduling in Millimeter-Wave Networks

We consider the distributed beam scheduling problem in mm-Wave networks where the base stations may belong to different operators and there is no centralized coordination among them. Our goal is to design distributed beam scheduling algorithms such that the network utility, which is defined as a logarithm function of the average throughput of the user equipment, can be maximized. We propose a non-cooperative game-based scheduling approach where the base stations are modeled as players that greedily maximize their own utilities. The Nash Equilibrium (NE) then provides a distributed solution to the network utility maximization problem. By employing the Lyapunov optimization, the asymptotic optimality of the proposed scheduling can be guaranteed. We prove the existence and provide sufficient conditions which guarantee the uniqueness of the NE by establishing an equivalence to the Variational Inequality (VI) problem. We also propose a parallel power adaptation algorithm which is proved to converge to the NE. Numerical results show the superiority of the proposed scheduling over several distributed baseline schemes.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

A Load Switching Group based Feeder-level Microgrid Energy Management Algorithm for Service Restoration in Power Distribution System

This paper presents a load switching group based energy management system (LSG-EMS) for operating microgrids on a distribution feeder powered by one or multiple grid-forming distributed energy resources. Loads on a distribution feeder are divided into load switching groups that can be remotely switched on and off. The LSG-EMS algorithm, formulated as a mixed-integer linear programming (MILP) problem, has an objective function of maximizing the served loads while minimizing the total number of switching actions. A new set of topology constraints are developed for allowing multiple microgrids to be formed on the feeder and selecting the optimal supply path. Customer comfort is accounted for by maximizing the supply duration in the customer preferred service period and enforcing a minimum service duration. The proposed method is demonstrated on a modified IEEE 33-bus system using actual customer data. Simulation results show that the LSG-EMS successfully coordinates multiple grid-forming sources by selecting an optimal supply topology that maximizes the supply period of both the critical and noncritical loads while minimizing customer service interruptions in the service restoration process.

Hu, Rongxing↗

DOE OSTI2019

Distinct Physiological Roles of the Three Ferredoxins Encoded in the Hyperthermophilic Archaeon Thermococcus kodakarensis

Control of electron flux is critical in both natural and bioengineered systems to maximize energy gains. Both small molecules and proteins shuttle high-energy, low-potential electrons liberated during catabolism through diverse metabolic landscapes. Ferredoxin (Fd) proteins—an abundant class of Fe-S-containing small proteins—are essential in many species for energy conservation and ATP production strategies. It remains difficult to model electron flow through complicated metabolisms and in systems in which multiple Fd proteins are present. The overlap of activity and/or limitations of electron flux through each Fd can limit physiology and metabolic engineering strategies. Here we establish the interplay, reactivity, and physiological role(s) of the three ferredoxin proteins in the model hyperthermophile Thermococcus kodakarensis . We demonstrate that the three loci encoding known Fds are subject to distinct regulatory mechanisms and that specific Fds are utilized to shuttle electrons to separate respiratory and energy production complexes during different physiological states. The results obtained argue that unique physiological roles have been established for each Fd and that continued use of T. kodakarensis and related hydrogen-evolving species as bioengineering platforms must account for the distinct Fd partnerships that limit flux to desired electron acceptors. Extrapolating our results more broadly, the retention of multiple Fd isoforms in most species argues that specialized Fd partnerships are likely to influence electron flux throughout biology. High-energy electrons liberated during catabolic processes can be exploited for energy-conserving mechanisms. Maximal energy gains demand these valuable electrons be accurately shuttled from electron donor to appropriate electron acceptor. Proteinaceous electron carriers such as ferredoxins offer opportunities to exploit specific ferredoxin partnerships to ensure that electron flux to critical physiological pathways is aligned with maximal energy gains. Most species encode many ferredoxin isoforms, but very little is known about the role of individual ferredoxins in most systems. Our results detail that ferredoxin isoforms make largely unique and distinct protein interactions in vivo and that flux through one ferredoxin often cannot be recovered by flux through a different ferredoxin isoform. The results obtained more broadly suggest that ferredoxin isoforms throughout biological life have evolved not as generic electron shuttles, but rather serve as selective couriers of valuable low-potential electrons from select electron donors to desirable electron acceptors.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

pnnl/ripples

A C++ Library for Influence Maximization Ripples is a software framework to study the Influence Maximization problem. Our goal with Ripples is to provide tools implementing fast and scalable state-of-the-art approximation algorithms to solve the influence maximization problem.

Minutoli, Marco↗

DOE OSTI2023

Data for Controlling Circuitry Underlies the Growth Optimization of Saccharomyces cerevisiae

Microbial growth emerges from coordinated synthesis of various cellular components from limited resources. In Saccharomyces cerevisiae , cyclic AMP (cAMP)-mediated signaling is shown to orchestrate cellular metabolism; however, it remains unclear quantitatively how the controlling circuit drives resource partition and subsequently shapes biomass growth. Here we combined experiment with mathematical modeling to dissect the signaling-mediated growth optimization of S. cerevisiae . We showed that, through cAMP-mediated control, the organism achieves maximal or nearly maximal steady-state growth during the utilization of multiple tested substrates as well as under perturbations impairing glucose uptake. However, the optimal cAMP concentration varies across cases, suggesting that different modes of resource allocation are adopted for varied conditions. Under settings with nutrient alterations, S. cerevisiae tunes its cAMP level to dynamically reprogram itself to realize rapid adaptation. Moreover, to achieve growth maximization, cells employ additional regulatory systems such as the GCN2-mediated amino acid control. This study establishes a systematic understanding of global resource allocation in S. cerevisiae , providing insights into quantitative yeast physiology as well as metabolic strain engineering for biotechnological applications.

Conversion↗

DOE OSTI2021

Attribute-Guided Adversarial Training for Robustness to Natural Perturbations

We report while existing work in robust deep learning has focused on small pixel-level norm-based perturbations, this may not account for perturbations encountered in several real world settings. In many such cases although test data might not be available, broad specifications about the types of perturbations (such as an unknown degree of rotation) may be known. We consider a setup where robustness is expected over an unseen test domain that is not i.i.d. but deviates from the training domain. While this deviation may not be exactly known, its broad characterization is specified a priori, in terms of attributes. We propose an adversarial training approach which learns to generate new samples so as to maximize exposure of the classifier to the attributes-space, without having access to the data from the test domain. Our adversarial training solves a min-max optimization problem, with the inner maximization generating adversarial perturbations, and the outer minimization finding model parameters by optimizing the loss on adversarial perturbations generated from the inner maximization. We demonstrate the applicability of our approach on three types of naturally occurring perturbations --- object-related shifts, geometric transformations, and common image corruptions. Our approach enables deep neural networks to be robust against a wide range of naturally occurring perturbations. We demonstrate the usefulness of the proposed approach by showing the robustness gains of deep neural networks trained using our adversarial training on MNIST, CIFAR-10, and a new variant of the CLEVR dataset.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Study of Integrable and Quasi-Integrable Sextupole Lattice

In order to maximize beam lifetime in circular particle accelerators, the nonlinear beam optics are optimized to maximize the dynamic aperture of the beam. The dynamic aperture (DA), which is a 6-D phase space volume of stable trajectories, depends on the strength of the nonlinearities in the machine, and is calculated via particle tracking. Current DA optimization processes include multi-objective genetic algorithm optimizers, and relies on minimizing the magnitudes of resonance driving terms (RDT), which are calculated from the nonlinear contribution to the one-turn-map. The process of searching through the parameter space for an ideal combination that maximizes DA is computationally strenuous. By setting up the sextupole channel such that it is resembles a symplectic integrator of a smooth Hamiltonian, with only a few sextupoles we are able to closely reproduce phase space trajectories of a smooth Hamiltonian up to the hyperbolic point. No chaos and resonances are observed if phase advance per one sextupole magnet in the channel does not exceed ~0.12x2 pi. Therefore, an important property of the suggested approach is the intrinsic elimination of the resonances, and minimization of corresponding RDTs.

43 PARTICLE ACCELERATORS↗

DOE OSTI2019

Conversion of Coal Wastes and Coal Plus Other Opportunity Fuel Mixtures, Such as Coal Plus Municipal Solids, to Produce Electricity and/or Liquid Fuels

For the foreseeable future, the Nation’s energy demand will continue to come largely from indigenous fossil energy resources and hydrocarbon fuels. Specifically waste coal plus other opportunity fuels need to be utilized as a feedstock to eliminate a waste stream and optimized to maximize energy yield and cleanly minimize pollutant emissions. Modular equipment is needed for installation in coal preparation locations, military installations, and research park facilities. Thermal decomposition of coal, biomass, and mixed solid waste (MSW) have been shown to reduce a waste stream while providing liquid and gaseous fuel products with low pollutant emissions. However, thermal decomposition processes have several challenges associated with preprocessing biomass and MSW, feeding and conveying material into the reactor, and post processing of syngas to remove undesirable products while upgrading to increase yield of high value products. Increasing total energy output from power plants by utilizing biomass and mixed wastes ultimately lowers energy costs, harmful environmental impacts of emissions, and has significant impacts on the energy security and sustainability of the U.S. economy. Entrained flow gasifiers (EFGs) produce very little CH4 and a wide range of H2/CO ratios (0.5–2.0) but are limited in their ability to effectively feed large biomass or MSW particles into the reactor. A solution to the feeding problems is to use pyrolysis torrefaction (PT) for conversion of waste materials to create a feedstock similar to coal and capable of grinding down and mixing with the coal feed. Mainstream experimentally explored reaction pathways for the conversion of coal waste plus municipal solids (CWPMS) and demonstrated a bench-scale reactor used for torrefaction of the municipal solid waste (MSW) to create a coal-like feed for blending with the coal waste. The material was processed in a pilot-scale EFG to determine product yield and emissions with CWPMS fuels, as well as the ash content and slagging properties of these feedstocks. The PT-EFG system was experimentally validated, where emissions and yield data were used to develop a high-fidelity process model and economic analysis. The following was accomplished in the Phase I: Determined optimal torrefaction process conditions for MSW and biomass through TGA; maximized heating value of fuel while maximizing final mass of torrefied product Demonstrated torrefaction of MSW and biomass feedstocks at 334°C, pulverized to uniform 74 µm particle size, and processed into coal-like feedstocks Demonstrated 8 lb/h pilot-scale EFG using MSW and biomass blends with waste coal; demonstrated 100% biomass in EFG Determined major effects of MSW torrefaction and co-gasifying high-ash coal waste-MSW blends have on pilot-scale EFG Demonstrated blending low-ash, low-sulfur torrefied biomass with high-ash waste bituminous and anthracite refuse coals generates a higher quality syngas compared to syngas from high-ash waste coals Demonstrated a high carbon conversion (> 99.5%) and syngas with 29.47% H2 content, and 0% CH4 content; greater water–gas shift occurs in EFG than predicted by equilibrium ASPEN Plus model Blended lower-ash, high-alkali biomass MSW to lower slag viscosities of the high-ash coal refuse sufficiently for better slag flow compared to feeding the high-ash coal Used low-sulfur biomass to greatly reduce the EFG syngas H2S concentrations and produce non-leachable slag and quench water with very little organic and trace metal contamination Developed a process model and TEA showing the modular PT EFG is cost competitive to existing power plants with the advantage of using low- or negative-value feedstocks such as waste coal stockpiles and non-landfilled MSW; providing a large incentive to implement an economical PT-EFG process

30 DIRECT ENERGY CONVERSION↗