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DOE OSTI2012

Strain-dependent Damage in Mouse Lung After Carbon Ion Irradiation

Purpose: To examine whether inherent factors produce differences in lung morbidity in response to carbon ion (C-ion) irradiation, and to identify the molecules that have a key role in strain-dependent adverse effects in the lung. Methods and Materials: Three strains of female mice (C3H/He Slc, C57BL/6J Jms Slc, and A/J Jms Slc) were locally irradiated in the thorax with either C-ion beams (290 MeV/n, in 6 cm spread-out Bragg peak) or with {sup 137}Cs {gamma}-rays as a reference beam. We performed survival assays and histologic examination of the lung with hematoxylin-eosin and Masson's trichrome staining. In addition, we performed immunohistochemical staining for hyaluronic acid (HA), CD44, and Mac3 and assayed for gene expression. Results: The survival data in mice showed a between-strain variance after C-ion irradiation with 10 Gy. The median survival time of C3H/He was significantly shortened after C-ion irradiation at the higher dose of 12.5 Gy. Histologic examination revealed early-phase hemorrhagic pneumonitis in C3H/He and late-phase focal fibrotic lesions in C57BL/6J after C-ion irradiation with 10 Gy. Pleural effusion was apparent in C57BL/6J and A/J mice, 168 days after C-ion irradiation with 10 Gy. Microarray analysis of irradiated lung tissue in the three mouse strains identified differential expression changes in growth differentiation factor 15 (Gdf15), which regulates macrophage function, and hyaluronan synthase 1 (Has1), which plays a role in HA metabolism. Immunohistochemistry showed that the number of CD44-positive cells, a surrogate marker for HA accumulation, and Mac3-positive cells, a marker for macrophage infiltration in irradiated lung, varied significantly among the three mouse strains during the early phase. Conclusions: This study demonstrated a strain-dependent differential response in mice to C-ion thoracic irradiation. Our findings identified candidate molecules that could be implicated in the between-strain variance to early hemorrhagic pneumonitis after C-ion irradiation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

Exploring drought-responsive crucial genes in Sorghum

Drought severely affects global food production. Sorghum is a typical drought-resistant model crop. Based on RNA-seq data for Sorghum with multiple time points and the gray correlation coefficient, this paper firstly selects candidate genes via mean variance test and constructs weighted gene differential co-expression networks (WGDCNs); then, based on guilt-by-rewiring principle, the WGDCNs and the hidden Markov random field model, drought-responsive crucial genes are identified for five developmental stages respectively. Enrichment and sequence alignment analysis reveal that the screened genes may play critical functional roles in drought responsiveness. A multilayer differential co-expression network for the screened genes reveals that Sorghum is very sensitive to pre-flowering drought. Furthermore, a crucial gene regulatory module is established, which regulates drought responsiveness via plant hormone signal transduction, MAPK cascades, and transcriptional regulations. The proposed method can well excavate crucial genes through RNA-seq data, which have implications in breeding of new varieties with improved drought tolerance.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

High-speed tunable generation of random number distributions using actuated perpendicular magnetic tunnel junctions

Perpendicular magnetic tunnel junctions (pMTJs) actuated by nanosecond pulses are emerging as promising devices for true random number generation (TRNG) due to their intrinsic stochastic behavior and high throughput. In this work, we demonstrate the tunability and quality of random number distributions generated by pMTJs operating at a frequency of 104 MHz. First, changing the pulse amplitude is used to systematically vary the probability bias. The variance of the resulting bitstreams closely matches the expected binomial distribution, demonstrating consistency with an underlying sequence of Bernoulli trials. Second, the quality of uniform distributions of 8-bit random numbers generated with a probability bias of 0.5 is considered. A reduced chi-square analysis of these data shows that only two XOR operations are sufficient to achieve this distribution with p-values greater than 0.05. Finally, we show that there is a correlation between long-term probability bias variations and pMTJ resistance. These findings suggest that variations in the characteristics of the pMTJ underlie the observed variation of probability bias. In conclusion, our results highlight the potential of stochastically actuated pMTJs for high-speed, tunable TRNG applications, showing the importance of the stability of pMTJ device characteristics in achieving reliable, long-term performance.

Magnetic tunnel junctions↗

DOE OSTI2019

Multiple Facets of the Poisson Distribution Applicable to Health Physics Measurements

This paper discusses several ways to view the standard Poisson distribution as applied to health physics scaler counts. The intent is not so much to present calculational details but rather to present some underlying concepts. Examples are provided that illustrate the various concepts for several types of specific measurements. The concepts presented involve purely Poisson-based contributions to variance; extra-Poisson variance is presently ignored, and any counting system would be presumed to function properly and without counting loss.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2013

MPACT Fast Neutron Multiplicity System Prototype Development

This document serves as both an FY2103 End-of-Year and End-of-Project report on efforts that resulted in the design of a prototype fast neutron multiplicity counter leveraged upon the findings of previous project efforts. The prototype design includes 32 liquid scintillator detectors with cubic volumes 7.62 cm in dimension configured into 4 stacked rings of 8 detectors. Detector signal collection for the system is handled with a pair of Struck Innovative Systeme 16-channel digitizers controlled by in-house developed software with built-in multiplicity analysis algorithms. Initial testing and familiarization of the currently obtained prototype components is underway, however full prototype construction is required for further optimization. Monte Carlo models of the prototype system were performed to estimate die-away and efficiency values. Analysis of these models resulted in the development of a software package capable of determining the effects of nearest-neighbor rejection methods for elimination of detector cross talk. A parameter study was performed using previously developed analytical methods for the estimation of assay mass variance for use as a figure-of-merit for system performance. A software package was developed to automate these calculations and ensure accuracy. The results of the parameter study show that the prototype fast neutron multiplicity counter design is very nearly optimized under the restraints of the parameter space.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

Systematic Biases in Weak Lensing Cosmology with the Dark Energy Survey

This thesis sets out a practical guide to applying shear measurements as a cosmological tool. We first present one of two science-ready galaxy shape catalogues from Year 1 of the Dark Energy Survey (DES Y1), which covers 1500 square degrees in four bands $griz$, with a median redshift of $0.59$. We describe the shape measurement process implemented by the DES Y1 imshape catalogue, which contains 21.9 million high-quality $r$-band bulge/disc fits. In Chapter 3 a new suite of image simulations, referred to as Hoopoe, are presented. The Hoopoe dataset is tailored to DES Y1 and includes realistic blending, spatial masks and variation in the point spread function. We derive shear corrections, which we show are robust to changes in calibration method, galaxy binning and variance within the simulated dataset. Sources of systematic uncertainty in the simulation-based shear calibration are discussed, leading to a final estimate of the $1\sigma$ uncertainties in the residual multiplica tive bias after calibration of 0.025. Chapter 4 describes an extension of the analysis on the Hoopoe simulations into a detailed investigation of the impact of galaxy neighbours on shape measurement and shear cosmology. Four mechanisms by which neighbours can have a non-negligible influence on shear measurement are identified. These effects, if ignored, would contribute a net multiplicative bias of $m \sim 0.03 - 0.09$ in DES Y1, though the precise impact will depend on both the measurement code and the selection cuts applied. We use the cosmological inference pipeline of DES Y1 to explore the cosmological implications of neighbour bias and show that omitting blending from the calibration simulation for DES Y1 would bias the inferred clustering amplitude $S_8 \equiv \sigma_8 (\omegam /0.3)^{0.5}$ by $1.5 \sigma$ towards low values. Finally, we use the Hoopoe simulations to test the effect of neighbour-induced spatial correlations in the multiplicative bias. We find the cosmo logical impact to be subdominant to statistical error at the! current level of precision. Another major uncertainity in shear cosmology is the accuracy of our ensemble redshift distributions. Chapter 5 presents a numerical investigation into the combined constraining power of cosmic shear, galaxy clustering and their cross-correlation in DES Y1, and the potential for internal calibration of redshift errors. Introducing a moderate uniform bias into the redshift distributions used to model the weak lensing (WL) galaxies is shown to produce a $> 2\sigma$ bias in $S_8$. We demonstrate that this cosmological bias can be eliminated by marginalising over redshift error nuisance parameters. Strikingly, the cosmological constraint of the combined dataset is largely undiminished by the loss of prior information on the WL distributions. We demonstrate that this implicit self-calibration is the result of complementary degeneracy directions in the combined data. In Chapter 6 we present the preliminary results of an investigation into galaxy intrin sic alignments. Using the DES Y1 data, we show a clear dependence in alignment amplitude on galaxy type, in agreement with previous results. We subject these findings to a series of initial robustness tests. We conclude with a short overview of the work presented, and discuss prospects for the future.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Ultrasound-assisted facile synthesis of a new tantalum(V) metal-organic framework nanostructure: Design, characterization, systematic study, and CO{sub 2} adsorption performance

This work presents a fast route for the preparation of a new Ta(V) metal-organic framework nanostructure with high surface area, significant porosity, and small size distribution. X-ray diffraction (XRD), scanning electron microscopy (SEM), Transition electron microscopy (TEM), energy dispersive spectrometer (EDS), thermo-gravimetric analysis (TGA), differential scanning calorimetry (DSC), fourier transform infrared spectroscopy (FTIR), CHNS/O elemental analyser, and Brunauer-Emmett-Teller (BET) surface area analysis were applied to characterize the synthesized product. Moreover, the influences of ultrasonic irradiation including temperature, time, and power on different features of the final products were systematically studied using 2{sup k-1} factorial design experiments, and the response surface optimization was used for determining the best welding parameter combination. The results obtained from analyses of variances showed that ultrasonic parameters affected the size distribution, thermal behaviour, and surface area of Ta-MOF samples. Based on response surface methodology, Ta-MOF could be obtained with mean diameter of 55 nm, thermal stability of 228 °C, and high surface area of 2100 m{sup 2}/g. The results revealed that the synthesized products could be utilized in various applications such as a novel candidate for CO{sub 2} adsorption. - Graphical abstract: A facile route was used for fabrication of a new metal -organic framework based on tantalum nanostructures that have high surface area, considerable porosity, homogenous morphology, and small size distribution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Non-Stationary Power System Forced Oscillation Analysis using Synchrosqueezing Transform

Non-stationary forced oscillations (FOs) have been observed in power system operations. However, most detection methods assume that the frequency of FOs is stationary. In this paper, we present a methodology for the analysis of nonstationary FOs. Firstly, Fourier synchrosqueezing transform (FSST) is used to provide a concentrated time-frequency representation of the signals that allows identification and retrieval of non-stationary signal components. To continue, the Dissipating Energy Flow (DEF) method is applied to the extracted components to locate the source of forced oscillations. The methodology is tested using simulated as well as real PMU data. In conclusion, the results show that the proposed FSST-based signal decomposition provides a systematic framework for the application of DEF Method to non-stationary FOs.

42 ENGINEERING↗

DOE OSTI2012

Stochastic approach to flat direction during inflation

We revisit the time evolution of a flat and non-flat direction system during inflation. In order to take into account quantum noises in the analysis, we base on stochastic formalism and solve coupled Langevin equations numerically. We focus on a class of models in which tree-level Hubble-induced mass is not generated. Although the non-flat directions can block the growth of the flat direction's variance in principle, the blocking effects are suppressed by the effective masses of the non-flat directions. We find that the fate of the flat direction during inflation is determined by one-loop radiative corrections and non-renormalizable terms as usually considered, if we remove the zero-point fluctuation from the noise terms.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Investigating genomic prediction strategies for grain carotenoid traits in a tropical/subtropical maize panel

Abstract Vitamin A deficiency remains prevalent on a global scale, including in regions where maize constitutes a high percentage of human diets. One solution for alleviating this deficiency has been to increase grain concentrations of provitamin A carotenoids in maize (Zea mays ssp. mays L.)—an example of biofortification. The International Maize and Wheat Improvement Center (CIMMYT) developed a Carotenoid Association Mapping panel of 380 inbred lines adapted to tropical and subtropical environments that have varying grain concentrations of provitamin A and other health-beneficial carotenoids. Several major genes have been identified for these traits, 2 of which have particularly been leveraged in marker-assisted selection. This project assesses the predictive ability of several genomic prediction strategies for maize grain carotenoid traits within and between 4 environments in Mexico. Ridge Regression-Best Linear Unbiased Prediction, Elastic Net, and Reproducing Kernel Hilbert Spaces had high predictive abilities for all tested traits (β-carotene, β-cryptoxanthin, provitamin A, lutein, and zeaxanthin) and outperformed Least Absolute Shrinkage and Selection Operator. Furthermore, predictive abilities were higher when using genome-wide markers rather than only the markers proximal to 2 or 13 genes. These findings suggest that genomic prediction models using genome-wide markers (and assuming equal variance of marker effects) are worthwhile for these traits even though key genes have already been identified, especially if breeding for additional grain carotenoid traits alongside β-carotene. Predictive ability was maintained for all traits except lutein in between-environment prediction. The TASSEL (Trait Analysis by aSSociation, Evolution, and Linkage) Genomic Selection plugin performed as well as other more computationally intensive methods for within-environment prediction. The findings observed herein indicate the utility of genomic prediction methods for these traits and could inform their resource-efficient implementation in biofortification breeding programs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

SU-E-T-426: Dose Delivery Accuracy in Breast Field Junction for Free Breath and Deep Inspiration Breath Hold Techniques

Purpose: The purpose of this work was to verify the accuracy of the dose distribution along the field junction in a half beam irradiation technique for breast cancer patients receiving radiation to the breast or chest wall (CW) and the supraclavicular LN region for both free breathing and deep inspiration breath hold (DIBH) technique. Methods: We performed in vivo measurements for nine breast cancer patients receiving radiation to the breast/CW and to the supraclavicular LN region. Six patients were treated to the left breast/CW using DIBH technique and three patients were treated to the right breast/CW in free breath. We used five microMOSFET dosimeters: three located along the field junction, one located 1 cm above the junction and the fifth microMOSFET located 1 cm below the junction. We performed consecutive measurements over several days for each patient and compared the measurements to the TPS calculation (Eclipse, Varian™). Results: The calculated and measured doses along the junction were 0.97±0.08 Gy and 1.02±0.14 Gy, respectively. Above the junction calculated and measured doses were 0.91±0.08 Gy and 0.98±0.09 Gy respectively, and below the junction calculated and measured doses were 1.70±0.15 Gy and 1.61±0.09 Gy, respectively. All differences were not statistically significant. When comparing calculated and measured doses for DIBH patients only, there was still no statistically significant difference between values for all dosimeter locations. Analysis was done using the Mann-Whitney Rank-Sum Test. Conclusion: We found excellent correlation between calculated doses from the TPS and measured skin doses at the junction of several half beam fields. Even for the DIBH technique, where there is more potential for variance due to depth of breath, there is no over or underdose along the field junction. This correlation validates the TPS, as well an accurate, reproducible patient setup.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Inferring microbial co-occurrence networks from amplicon data: a systematic evaluation

Microbes commonly organize into communities consisting of hundreds of species involved in complex interactions with each other. 16S ribosomal RNA (16S rRNA) amplicon profiling provides snapshots that reveal the phylogenies and abundance profiles of these microbial communities. These snapshots, when collected from multiple samples, can reveal the co-occurrence of microbes, providing a glimpse into the network of associations in these communities. However, the inference of networks from 16S data involves numerous steps, each requiring specific tools and parameter choices. Moreover, the extent to which these steps affect the final network is still unclear. In this study, we perform a meticulous analysis of each step of a pipeline that can convert 16S sequencing data into a network of microbial associations. Through this process, we map how different choices of algorithms and parameters affect the co-occurrence network and identify the steps that contribute substantially to the variance. We further determine the tools and parameters that generate robust co-occurrence networks and develop consensus network algorithms based on benchmarks with mock and synthetic data sets. The Microbial Co-occurrence Network Explorer, or MiCoNE (available at https://github.com/segrelab/MiCoNE) follows these default tools and parameters and can help explore the outcome of these combinations of choices on the inferred networks. We envisage that this pipeline could be used for integrating multiple data sets and generating comparative analyses and consensus networks that can guide our understanding of microbial community assembly in different biomes.

16S rRNA↗

DOE OSTI2023

Decay Dose Shielding Analysis with Hybrid Unstructured Mesh/Constructive Solid Geometry Monte Carlo Calculation and ADVANTG Acceleration

Here, the target segments of the Oak Ridge National Laboratory Second Target Station (STS) neutron production facility become highly activated due to spallation reactions or nuclei transmutation by primary protons and emitted neutrons. Once the target segments are removed from their location within the core vessel, decay dose rates must be accurately quantified to determine the shielding configurations of remote-handling tools and transport casks and to aid in planning maintenance activities. For this analysis, we utilized a hybrid unstructured mesh (UM)/constructive solid geometry approach for calculating spallation products and neutron fluxes, activation calculations using the AARE package that includes the CINDER2008 activation code to calculate the decay photon source at different cooling times, and the ADVANTG code to accelerate the final decay photon transport calculation. Both Type 316 stainless steel (SS-316) and lead were investigated as candidates for shielding materials. The decay photon transport calculation through the thick SS-316 or lead shields exhibited between 25 and 30 orders-of-magnitude attenuations in the radial direction, depending on the shield. Such a difficult shielding calculation required advanced variance reduction. ADVANTG has some missing features, which limits its usability in spallation neutron source applications. It does not support volumetric sources created for MCNP6.2 UM capability. An approximate source was created for this problem. Not only was this approximate source needed for running the ADVANTG calculation to generate the weight windows, but also it was essential to develop source biasing (SB) parameters that were crucial for dramatically accelerating the decay photon transport in this problem. With this approximate source, the analysis was completed in a very reasonable computational time, and the design of the STS remote-handling equipment was finalized. This paper compares the efficiency of Monte Carlo simulations with different weight window and SB parameters calculated using different approximate ADVANTG calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2015

IMPROVING COSMOLOGICAL DISTANCE MEASUREMENTS USING TWIN TYPE IA SUPERNOVAE

We introduce a method for identifying “twin” Type Ia supernovae (SNe Ia) and using them to improve distance measurements. This novel approach to SN Ia standardization is made possible by spectrophotometric time series observations from the Nearby Supernova Factory (SNfactory). We begin with a well-measured set of SNe, find pairs whose spectra match well across the entire optical window, and then test whether this leads to a smaller dispersion in their absolute brightnesses. This analysis is completed in a blinded fashion, ensuring that decisions made in implementing the method do not inadvertently bias the result. We find that pairs of SNe with more closely matched spectra indeed have reduced brightness dispersion. We are able to standardize this initial set of SNfactory SNe to 0.083 ± 0.012 mag, implying a dispersion of 0.072 ± 0.010 mag in the absence of peculiar velocities. We estimate that with larger numbers of comparison SNe, e.g., using the final SNfactory spectrophotometric data set as a reference, this method will be capable of standardizing high-redshift SNe to within 0.06–0.07 mag. These results imply that at least 3/4 of the variance in Hubble residuals in current SN cosmology analyses is due to previously unaccounted-for astrophysical differences among the SNe.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Partially coherent ptychography by gradient decomposition of the probe

Coherent ptychographic imaging experiments often discard the majority of the flux from a light source to define the coherence of the illumination. Even when the coherent flux is sufficient, the stability required during an exposure is another important limiting factor. Partial coherence analysis can considerably reduce these limitations. A partially coherent illumination can often be written as the superposition of a single coherent illumination convolved with a separable translational kernel. This article proposes the gradient decomposition of the probe (GDP), a model that exploits translational kernel separability, coupling the variances of the kernel with the transverse coherence. An efficient first-order splitting algorithm ( GDP-ADMM ) for solving the proposed nonlinear optimization problem is described. Numerical experiments demonstrate the effectiveness of the proposed method with Gaussian and binary kernel functions in fly-scan measurements. Remarkably, GDP-ADMM using nanoprobes produces satisfactory results even when the ratio between the kernel width and the beam size is more than one, or when the distance between successive acquisitions is twice as large as the beam width.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Estimation of Turbulence Parameters from Scanning Lidars and in-situ Instrumentation in the Perdigao 2017 Campaign

The understanding of the sources, spatial distribution and temporal variability of turbulence in the atmospheric boundary layer (ABL) and improved simulation of its forcing processes require observations in a broad range of terrain types and atmospheric conditions. In this study, we estimate turbulence kinetic energy (TKE) dissipation rate using multiple techniques, including traditional in-situ measurements of sonic anemometers on meteorological towers, a hot-wire anemometer on a tethered lifting system (TLS), as well as remote-sensing retrievals from a vertically staring lidar and two lidars performing range-height indicator (RHI) scans. For the retrieval of e from the lidar RHI scans, we introduce a modification of the Doppler Spectral Width (DSW) method. This method uses spatio-temporal averages of the variance of the line-of-sight (LOS) velocity and the turbulent broadening of the Doppler backscatter spectrum. We validate this method against the observations from the other instruments, also including uncertainty estimations for each method. The synthesis of the results from all instruments enables a detailed analysis of the spatial and temporal variability of e across a valley between two parallel ridges at the Perdigao 2017 campaign. We find that the shear zones above and below nighttime low-level jets (LLJ) experience turbulence enhancements, as does the wake of a wind turbine (WT). We analyze in detail how e varies in the early morning of 14 June 2017, when the turbulence in the valley, approximately eleven rotor diameters downstream of the WT, is still significantly enhanced by the WT wake.

17 WIND ENERGY↗

DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

29 ENERGY PLANNING, POLICY, AND ECONOMY↗