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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Gaussian Mean Field Lattice Gas

We study rigorously a lattice gas version of the Sherrington–Kirckpatrick spin glass model. In discrete optimization literature this problem is known as unconstrained binary quadratic programming and it belongs to the class NP-hard. We prove that the fluctuations of the ground state energy tend to vanish in the thermodynamic limit, and we give a lower bound of such ground state energy. Then we present a heuristic algorithm, based on a probabilistic cellular automaton, which seems to be able to find configurations with energy very close to the minimum, even for quite large instances.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

SimCCS: An open-source tool for optimizing CO 2 capture, transport, and storage infrastructure

Commercial-scale carbon capture and storage (CCS) technology will involve deploying infrastructure on a massive and costly scale. This effort will require careful and comprehensive planning to ensure that capture locations, storage sites, and the dedicated CO 2 distribution pipelines are selected in a robust and cost-effective manner. Presented in 2009, SimCCS is an optimization model for integrated system design that enables researchers, stakeholders, and policy makers to design CCS infrastructure networks. SimCCS 2.0 is a complete, ground-up redesign that is now a portable software package, useable and shareable by the CCS research, industrial, policy, and public communities. SimCCS 2.0 integrates multiple new capabilities including a refined optimization model, novel candidate network generation techniques, and optional integration with high-performance computing platforms. Accessing user-provided CO 2 source, sink, and transportation data, SimCCS 2.0 creates candidate transportation routes and formalizes an optimization problem that determines the most cost-effective CCS system design. This optimization problem is further solved either through a high-performance computing interface, or through third-party software on a local desktop computing platform. Finally, SimCCS 2.0 employs an open-access geographic information system framework to enable analysis and visualization capabilities. SimCCS 2.0 is written in Java and is publicly available via GitHub to encourage collaboration, modification, and community development.

42 ENGINEERING↗
DOE OSTI2022

Improvement of two-phase closure models in CTF using Bayesian inference

Under the Consortium for Advanced Simulation of Light Water Reactors (CASL) program, extensive capabilities have been developed in CTF to analyze light-water reactors (LWRs) for normal operating conditions, departure from nucleate boiling (DNB), and system transients. However, further improvements are required in the modeling and simulation of boiling water reactors (BWRs), which is a focus of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. In this work, CTF validation results were used to optimize selected modeling coefficients by calibrating to experimental data using a Bayesian inference approach. Here, calibration studies were conducted to improve (vapor) void fraction prediction without worsening the two-phase pressure drop prediction, as well as to improve the two-phase pressure drop prediction. Calibration was performed for interfacial drag and wall shear models. Surrogates were developed to alleviate the computational expense required for sampling the parameter space using Markov chain Monte Carlo (MCMC). An assessment performed with calibrated models demonstrated an improvement of CTF in its prediction of key parameters such as void fraction and two-phase pressure drop.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Characterization of onset of parametric decay instability of lower hybrid waves

The goal of the lower hybrid current drive (LHCD) program on Alcator C-Mod is to develop and optimize ITER-relevant steady-state plasmas by controlling the current density profile. Using a 4×16 waveguide array, over 1 MW of LH power at 4.6 GHz has been successfully coupled to the plasmas. However, current drive efficiency precipitously drops as the line averaged density (nÐœ„{sub e}) increases above 10{sup 20}m{sup −3}. Previous numerical work shows that the observed loss of current drive efficiency in high density plasmas stems from the interactions of LH waves with edge/scrape-off layer (SOL) plasmas [Wallace et al., Physics of Plasmas 19, 062505 (2012)]. Recent observations of parametric decay instability (PDI) suggest that non-linear effects should be also taken into account to fully characterize the parasitic loss mechanisms [Baek et al., Plasma Phys. Control Fusion 55, 052001 (2013)]. In particular, magnetic configuration dependent ion cyclotron PDIs are observed using the probes near nÐœ„{sub e}≈1.2×10{sup 20}m{sup −3}. In upper single null plasmas, ion cyclotron PDI is excited near the low field side separatrix with no apparent indications of pump depletion. The observed ion cyclotron PDI becomes weaker in inner wall limited plasmas, which exhibit enhanced current drive effects. In lower single null plasmas, the dominant ion cyclotron PDI is excited near the high field side (HFS) separatrix. In this case, the onset of PDI is correlated with the decrease in pump power, indicating that pump wave power propagates to the HFS and is absorbed locally near the HFS separatrix. Comparing the observed spectra with the homogeneous growth rate calculation indicates that the observed ion cyclotron instability is excited near the plasma periphery. The incident pump power density is high enough to overcome the collisional homogeneous threshold. For C-Mod plasma parameters, the growth rate of ion sound quasi-modes is found to be typically smaller by an order of magnitude than that of ion cyclotron quasi-modes. When considering the convective threshold near the plasma edge, convective growth due to parallel coupling rather than perpendicular coupling is likely to be responsible for the observed strength of the sidebands. To demonstrate the improved LHCD efficiency in high density plasmas, an additional launcher has been designed. In conjunction with the existing launcher, this new launcher will allow access to an ITER-like high single pass absorption regime, replicating the J{sub LH}(r) expected in ITER. The predictions from the time domain discharge scenarios, in which the two launchers are used, will be also presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Characterization of the onset of ion cyclotron parametric decay instability of lower hybrid waves in a diverted tokamak

The goal of the lower hybrid current drive (LHCD) program on Alcator C-Mod is to develop and optimize reactor-relevant steady-state plasmas by controlling current density profile. However, current drive efficiency precipitously decreases as the line averaged density (n{sup ¯}{sub e}) increases above ∼1 × 10{sup 20} m{sup −3}. Previous simulations show that the observed loss of current drive efficiency in high density plasmas stems from the interactions of LH waves with edge/scrape-off layer plasmas [Wallace et al., Phys. Plasmas 19, 062505 (2012)]. A recent observation [Baek et al., Plasma Phys. Controlled Fusion 55, 052001 (2013)] shows that the configuration dependent ion cyclotron parametric decay instability (PDI) is excited in the density range where the discrepancy between the experiments and simulations remains. Comparing the observed spectra with the homogeneous growth rate spectra indicates that the observed ion cyclotron PDI can be excited not only at the low-field-side but also at the high-field-side (HFS) edge of the tokamak. The model analysis shows that a relevant PDI process to Alcator C-Mod LHCD experiments is decay into ion cyclotron quasi-mode driven by parallel coupling. The underlying cause of the observed onset of ion cyclotron PDI is likely due to the weaker radial penetration of the LH wave in high density plasmas, which can lead to enhanced convective growth. Configuration-dependent PDIs are found to be correlated with different edge density profiles in different magnetic configurations. While the HFS edge of the tokamak can be potentially susceptible to PDI, as evidenced by experimental observations and ray-tracing analyses, enhancing single-pass absorption is expected to help recover the LHCD efficiency at reactor-relevant densities because it could suppress several parasitic loss mechanisms that are exacerbated in multi-pass regimes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Secondary Voltage Control Via Demand-Side Energy Storage with Temporal Logic Specifications

This paper proposes a secondary voltage control method that can handle the temporal logic specifications (TLSs). The control objective is to schedule a control signal for energy storage system (ESS) such that the voltage variation of a defined critical bus satisfies TLSs. The TLS allows definitions of set and timing constraints at the same time, such as a finite-time restoration. A simplified analytical model is derived to describe the voltage variation of critical buses. Based on this model, a numerical optimal control problem is formulated as a mixed integer linear program to generate the proper control input for the ESS. The proposed control is verified on a lumped distribution system model. With this control diagram, supportive controllers can be easily designed to make voltage behaviors comply with grid codes and avoid unnecessary relay actions.

Zhang, Yichen↗
DOE OSTI2019

A VSM-Based DER Dispatch MINLP for Volt-VAR Control in Unbalanced Power Distribution Systems

This paper presents an optimal dispatch algorithm to coordinate customer-owned controllable loads and smart solar inverters with utility-owned voltage regulators and capacitors to meet voltage control objectives. The optimization problem is formulated as a mixed-integer nonlinear programming (MINLP) problem. A voltage sensitivity matrix (VSM) is used to linearize the effect of control actions on the voltage at customer nodes when solving the MINLP. The VSM is recalculated at each time step to improve the computational accuracy. Both discrete switching actions of the capacitor and VRs and the continuous adjustment of real and reactive power from load and smart inverters are considered in the MINLP volt-var problem formulation. The objective function minimizes the cost of all control actions and the magnitude of voltage fluctuations from the previous time period. Constraints ensure that the voltage at each node is maintained within ANSI limits and the feeder power factor is controlled within the desired range. The algorithm is tested using an actual 3-phase unbalanced distribution feeder model. Simulation results demonstrate that the proposed algorithm is computationally feasible on real circuits and improves voltage control while minimizing operational costs.

McEntee, Catie↗
DOE OSTI2021

Ensemble Learning Based Convex Approximation of Three-Phase Power Flow

Though the convex optimization has been widely used in power systems, it still cannot guarantee to yield a tight (accurate) solution to some problems. To mitigate this issue, this paper proposes an ensemble learning based convex approximation for alternating current (AC) power flow equations that differs from the existing convex relaxations. The proposed approach is based on three-phase quadratic power flow equations in rectangular coordinates. To develop this data-driven convex approximation of power flows, the polynomial regression (PR) is first deployed as a basic learner to fit convex relationships between the independent and dependent variables. Then, ensemble learning algorithms such as gradient boosting (GB) and bagging are introduced to combine learners to boost model performance. Based on the learned convex approximation of power flow, optimal power flow (OPF) is formulated as a convex quadratic programming problem. The simulation results on IEEE standard cases of both balanced and unbalanced systems show that, in the context of solving OPF, the proposed data-driven convex approximation outperforms the conventional semi-definite programming (SDP) relaxation in both accuracy and computational efficiency, especially in the cases that the conventional SDP relaxation fails

Convex approximation↗
DOE OSTI2024

Nitrogen acquisition and retention pathways in sustainable perennial bioenergy grass cropping systems

Abstract Perennial tall grasses show promise as bioenergy crops due to high productivity and efficient nutrient use. Ongoing research on bioenergy grasses seeks to reduce their reliance on synthetic nitrogen (N) fertilizer, the manufacture of which relies on fossil fuel combustion. Excessive use of fertilizers also causes adverse environmental consequences and leads to the evolutionary loss of plant traits beneficial to sustainable N cycle. Notably, perennial tall grasses have exhibited the potential to maintain high biomass yield without the need for N fertilizer or causing soil N depletion. Perennial grasses can be adept at interacting with their microbial partners to facilitate N acquisition and retention via mechanisms such as biological N fixation and nitrification inhibition. These inherent N management traits should be preserved and optimized at the this early stage of bioenergy grass breeding programs. This review examines the impact of external N on bioenergy grass production and explores the potential of leveraging advantageous N‐cycling attributes of perennial tall grasses, laying groundwork for future management and research efforts. With minimized dependency on external N input, the cultivation of perennial energy grasses will pave the way toward more resilient agricultural systems and play a significant role in addressing key global energy and environmental challenges.

Agriculture↗
DOE OSTI2019

Inpatient Opioid Use After Pancreatectomy: Opportunities for Reducing Initial Opioid Exposure in Cancer Surgery Patients

Background: Despite advances in enhanced surgical recovery programs, strategies limiting postoperative inpatient opioid exposure have not been optimized for pancreatic surgery. The primary aims of this study were to analyze the magnitude and variations in post-pancreatectomy opioid administration and to characterize predictors of low and high inpatient use. Methods: Clinical characteristics and inpatient oral morphine equivalents (OMEs) were downloaded from electronic records for consecutive pancreatectomy patients at a high-volume institution between March 2016 and August 2017. Regression analyses identified predictors of total OMEs as well as highest and lowest quartiles. Results: Pancreatectomy was performed for 158 patients (73% pancreaticoduodenectomy). Transversus abdominus plane (TAP) block was performed for 80% (n = 127) of these patients, almost always paired with intravenous patient-controlled analgesia (IV-PCA), whereas 15% received epidural alone. All the patients received scheduled non-opioid analgesics (median, 2). The median total OME administered was 423 mg (range 0–4362 mg). Higher total OME was associated with preoperative opioid prescriptions (p < 0.001), longer hospital length of stay (LOS; p < 0.001), and no epidural (p = 0.006). The lowest and best quartile cutoff was 180 mg of OME or less, whereas the highest and worst quartile cutoff began at 892.5 mg. After adjustment for inpatient team, only epidural use [odds ratio (OR) 0.3; p = 0.04] predicted lowest-quartile OME. Preoperative opioid prescriptions (OR 8.1; p < 0.001), longer operative time (OR 3.4; p = 0.05), and longer LOS (OR 1.1; p = 0.007) predicted highest-quartile OME. Conclusions: Preoperative opioid prescriptions and longer LOS were associated with increased inpatient OME, whereas epidural use reduced inpatient OME. Understanding the predictors of inpatient opioid use and the variables predicting the lowest and highest quartiles can inform decision-making regarding preoperative counseling, regional anesthetic block choice, and novel inpatient opioid weaning strategies to reduce initial postoperative opioid exposure.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

North Carolina Water Utility Builds Resilience with Distributed Energy Resources

As the frequency and duration of grid outages increase, backup power systems are becoming more important for ensuring that critical infrastructure continues to provide essential services. Most facilities rely on diesel generators, which may be ineffective during long outages owing to limited fuel supplies and high generator failure rates. Distributed energy resources such as solar, storage, and combined-heat-and-power systems, coupled with on-site biofuel production, offer an alternative source of on-site generation that can provide both cost savings and resilience (i.e., the ability to respond to catastrophic events with longer-term consequences). A mixed-integer linear program minimizes costs and maximizes resilience at a wastewater treatment plant in Wilmington, North Carolina. We find that the plant can reduce life-cycle energy costs by 3.1% through the installation of a hybrid combined-heat-and-power, photovoltaic, and storage system. When paired with existing diesel generators, this system can sustain full load for seven days while saving $664,000 over 25 years and reducing diesel fuel use by 48% compared with the diesel-only solution. This analysis informed a decision by the Cape Fear Public Utility Authority to allocate funds for the implementation of a combined-heat-and-power system at the wastewater treatment plant in fiscal year 2023. Finally, the benefits of deploying hybrid combined-heat-and-power technologies and the utilization of on-site biofuel production extend, on a national scale, to thousands of wastewater treatment facilities and other types of critical infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Overview: Development of the National Ignition Facility and the Transition to a User Facility for the Ignition Campaign and High Energy Density Scientific Research

The National Ignition Facility (NIF) at Lawrence Livermore National Laboratory has been operational since March 2009 and has been transitioning to a user facility supporting ignition science, high energy density stockpile science, national security applications, and fundamental science. The facility has achieved its design goal of 1.8 MJ and 500 TW of 3ω light on target, and has performed target experiments with 1.9 MJ at peak powers of 410 TW. The National Ignition Campaign (NIC), established by the U.S. National Nuclear Security Administration in 2005, was responsible for transitioning NIF from a construction project to a national user facility. Besides the operation and optimization of the use of the NIF laser, the NIC program was responsible for developing capabilities including target fabrication facilities; cryogenic layering capabilities; over 60 optical, X-ray, and nuclear diagnostic systems; experimental platforms; and a wide range of other NIF facility infrastructure. This study provides a summary of some of the key experimental results for NIF to date, an overview of the NIF facility capabilities, and the challenges that were met in achieving these capabilities. Finally, they are covered in more detail in the papers that follow.

42 ENGINEERING↗
DOE OSTI2023

JSPEC: A Program for IBS and Electron Cooling Simulation

JSPEC (JLab Simulation Package on Electron Cooling) is an open-source C++ program developed at Jefferson Lab to simulate the evolution of the ion beam under the intrabeam scattering effect and/or the electron cooling effect. JSPEC includes various models of the ion beam, the electron beam, and the friction force, aiming to reflect the latest advances in the field and to provide a useful tool to the community. JSPEC has been benchmarked against other cooling simulation codes and experimental data. It has been used to support the cooler design for JLEIC, an earlier JLab design for the Electron-Ion Collider. A Python wrapper of the C++ code, pyJSPEC, for Python 3.x environment has also been developed and released. It allows users to run JSPEC simulations in a Python environment and makes it possible for JSPEC to collaborate with other accelerator and beam modeling programs, as well as plentiful Python tools in data visualization, optimization, machine learning, etc. In this report, we introduce the features of JSPEC, with a focus on the latest development, and demonstrate how to use JSPEC and pyJSPEC with sample codes and numerical examples.

Accelerator Physics↗
DOE OSTI2022

pyJSPEC - A Python Module for IBS and Electron Cooling Simulation

The intrabeam scattering is an important collective effect that can deteriorate the property of a high-intensity beam and electron cooling is a method to mitigate the IBS effect. JSPEC (JLab Simulation Package on Electron Cooling) is an open-source C++ program developed at Jefferson Lab, which simulates the evolution of the ion beam under the IBS and/or the electron cooling effect. The Python wrapper of the C++ code, pyJSPEC, for Python 3.x environment has been recently developed and released. It allows the users to run JSPEC simulations in a Python environment. It also makes it possible for JSPEC to collaborate with other accelerator and beam modeling programs as well as plentiful python tools in data visualization, optimization, machine learning, etc. In this paper, we will introduce the features of pyJSPEC and demonstrate how to use it with sample codes and numerical results.

Zhang, H.↗
DOE OSTI2017

Integrated Smart Distribution RD&D Project Final Technical Report

Title XIII of the Energy Independence and Security Act of 2007 (EISA), tasked OE with accelerating the commercialization, deployment and integration of advanced digital systems that are needed to modernize the nation’s electricity delivery network for enhanced interoperability and cyber security. To support this mandated task, a goal of the SGR&D Program is to develop technology with the ability to dynamically optimize grid operations and resources and incorporate demand response and consumer participation. The majority of historical research and development in the domain of distribution management systems (DMS) had focused on classical, radial and passive networks with one-way power flow from transmission to distribution systems and thus to the end customer. With the focus on customers, a bottom-up approach required a completely new thinking in real-time operations, and automation, of smart distribution systems. Thus, the GE team embarked on a project with a plan of two distinct phases. Work during the first phase concentrated on research and development (R&D) for the first three years. The second phase, lasting approximately two years, accomplished the demonstration of the use cases developed during the first phase, with further sharing and dissemination of the research at industry events. The consolidated technical scope of the project can be summarized into the following six areas: Advanced distribution modeling capability to accurately simulate/model smart grid operations. Accurate representation of the distribution system in real- or near real-time (capture real-time topology). Interoperability with, and seamless communication between, other management systems and databases used by the utility Simulation of distribution systems based on real-time operational planning to analyze the benefits of smart grid assets. Integration of network, market, and renewable resource models for next generation DMS. Management and forecasting of DER (Distributed Generation, Storage, Demand Response).

14 SOLAR ENERGY↗
DOE OSTI2023

High Efficacy, Long Lifetime Flexible White OLED Lighting Panels

In this project, OLEDWorks and partners made significant progress in advancing OLED light extraction technology. Improving light extraction efficiency remains one of the most important research topics for OLEDs. Current state-of-the-art white OLED products extract only about 50% of the photons that are generated within the device. Promising new light extraction concepts, such as those based on sub electrode micro lens arrays (SEMLAs), were explored in this project with the potential to achieve extraction efficiency of 60% or higher. Flexible thin glass substrates with integrated SEMLAs were successfully fabricated and scaled to large area. When combined with optimized high efficiency stacked white OLED structures, we achieved the program goals of 120 LPW efficacy and long lifetime more than 100,000 hours.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Development of Scalable Coastal and Offshore Macroalgal Farming

The US DOE/ARPA-E MARINER program funded a four-year project to determine an optimal way to grow kelps in large, nearshore and offshore arrays for the eventual purpose of biofuel production with the goal of keeping the cost below $\$$80 USD per dry metric ton of kelp. This project specifically looked at how Saccharina latissima can be grown in the Gulf of Alaska to reach that goal. There were three major aspects of the research: 1) optimizing nursery production and seeding lines for outplanting, 2) designing an economical, modular outplanting structure and 3) developing methods to efficiently harvest the product. Farm designs were based on catenary structures and the use of spreader bars with variable spacing of grow lines and line types. The spacing of the grow lines makes a difference in the yield. Grow line spacing of ≥1.5m showed about a 50% increase in kg/m. There was no statistical difference in the growth of Saccharina latissima whether in the middle or the outside of the array, but the line type and perhaps line thickness can make a difference in yield. Sagging caused by the weight of the mature fronds resulted in lower growth at depth. Various harvesting approaches for mature kelps were tested by collaborating farmers. One promising innovation is the use of large bags for holding the freshly harvested fronds. Although the weight of the fronds on the growlines causes the lines to sink, the bags packed with the harvested fronds float, allowing for easy loading to the transfer vessel. Another advance in harvesting is a specially built harvest vessel, the Harvest Buddy, allowing a more mechanized and faster way to harvest. A significant aspect of this project was the TTO/T2M. Several different outreach activities were performed by the Alaska Fisheries Development Foundation and GreenWave. A techno-economic assessment (TEA) using our data has pointed to solutions to reach the $\$$80 goal. A second phase of this project involved the co-culture of two different species of kelps. Interest in farming kelps has grown beyond using kelp for food, feed or biofuels. There is considerable interest in generating biomass from seaweed for use in bioplastics and other products that would substitute for petroleum-derived products. For these uses to be viable, large amounts of biomass are needed. Very large kelp farms can be expensive to build and maintain, leading to the need to optimize the biomass per unit area. Although close spacing of growlines can lead to poor growth, a viable approach may be to grow two species of kelps together: one that hangs down and one that is buoyant, growing up. This system would increase the spacing in three dimensions. In Alaska, Saccharina latissima is commonly grown hanging down from longlines. One of the buoyant Alaskan kelps is Nereocystis luetkeana. Because there are commercial uses for wild-harvested Nereocystis in Alaska, we undertook a preliminary trial in Kodiak, Alaska that grew both Saccharina and Nereocystis in the same longline array. Closely spaced lines were seeded the first week of February 2023 and set at 3m below the surface. The arrays were harvested in late June 2023. Despite having 45% fewer grow-lines, the total yield of the Nereocystis on the combined arrays was statistically similar to the Nereocystis only arrays. Total yields were greatest on the combined arrays, followed by the Nereocystis only and Saccharina only arrays. These results may have significance for large scale macroalgal production.

09 BIOMASS FUELS↗
DOE OSTI2025

Project Planning for Community Resilience: Aquinnah and Chilmark, Massachusetts

This report presents the findings of an energy system planning study for the towns of Aquinnah and Chilmark, MA, on the island of Martha’s Vineyard, conducted under the U.S. Department of Energy ETIPP program. The study used the DER-CAM model to optimize the deployment of PV and battery microgrids to enhance energy resilience against power outages, particularly winter storms. Key findings show that PV is highly cost-effective and delivers net annual savings. However, due to limited rooftop space and low winter solar output, PV and battery storage alone cannot support the full critical load during outages. Solutions incorporating conventional backup generators were found to be more economically viable for achieving 100% critical load support.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗