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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Measuring the impact ionization and charge trapping probabilities in SuperCDMS HVeV phonon sensing detectors

A 0.93 g 1×1×0.4 cm 3 SuperCDMS silicon HVeV detector operated at 30 mK was illuminated by 1.91 eV photons using a room temperature pulsed laser coupled to the cryostat via fiber optic. In this work, the detector’s response under a variety of specific operating conditions was used to study the detector leakage current, charge trapping, and impact ionization in the high-purity Si substrate. The measured probabilities for a charge carrier in the detector to undergo charge trapping (0.713±0.093%) or cause impact ionization (1.576±0.110%) were found to be nearly independent of bias polarity and charge-carrier type (electron or hole) for substrate biases of ±140 V.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Position-dependent matter density probability distribution function

Here, we introduce the position-dependent probability distribution function (PDF) of the smoothed matter field as a cosmological observable. In comparison to the PDF itself, the spatial variation of the position-dependent PDF is simpler to model and has distinct dependence on cosmological parameters. We demonstrate that the position-dependent PDF is characterized by variations in the local mean density, and we compute the linear response of the PDF to the local density using separate universe N-body simulations. The linear response of the PDF to the local density field can be thought of as the linear bias of regions of the matter field selected based on density. We provide a model for the linear response, which accurately predicts our simulation measurements. We also validate our results and test the separate universe consistency relation for the local PDF using global universe simulations. We find excellent agreement between the two, and we demonstrate that the separate universe method gives a lower variance determination of the linear response.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Position-dependent Voronoi probability distribution functions for matter and halos

Here, we measure the Voronoi density probability distribution function (PDF) for both dark matter and halos in N-body simulations. For the dark matter, Voronoi densities represent the matter density field smoothed on a uniform mass scale, which approximates the Lagrangian density field. For halos, the Voronoi densities contain information about the local environment of each halo. We measure the halo virial masses, the total amount of dark matter within each halo Voronoi cell, and the halo Voronoi cell volumes, and we show how halo abundances depend on these three quantities. We then study the position-dependent Voronoi density PDF, measured within finite subregions of the Universe, using separate universe simulations. We demonstrate that the spatial variation of the position-dependent PDF is due to large-scale density fluctuations, indicating that the position-dependent PDF is a biased tracer of large-scale structure. We measure this bias for the dark matter, and interpret it as the bias of regions of the Lagrangian density field that are selected based on density. For the halos, this bias can be interpreted as a form of assembly bias. We present the mapping from late-time to early-time Voronoi density for each simulation dark matter particle, which is highly stochastic. We compare the median of this stochastic map with spherical collapse calculations and discuss challenges involved in modeling the evolution of the density field on these scales.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Accelerating accurate simulations of calorimeter showers with normalizing flows and probability density distillation

Recently, we introduced caloflow, a high-fidelity generative model for GEANT4 calorimeter shower emulation based on normalizing flows. Here, we present caloflow v2, an improvement on our original framework that speeds up shower generation by a further factor of 500 relative to the original. The improvement is based on a technique called probability density distillation, originally developed for speech synthesis in the machine learning literature, and which we develop further by introducing a set of powerful new loss terms. We demonstrate that caloflow v2 preserves the same high fidelity as the original using qualitative (average images, histograms of high-level features) and quantitative (classifier metric between geant4 and generated samples) measures. The result is a generative model for calorimeter showers that matches the state of the art in speed (a factor of 10 4 faster than GEANT4) and greatly surpasses the previous state of the art in fidelity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Cosmological constraints from the Subaru Hyper Suprime-Cam year 1 shear catalogue lensing convergence probability distribution function

Here we utilize the probability distribution function (PDF) of normalized convergence maps reconstructed from the Subaru Hyper Suprime-Cam (HSC) year 1 shear catalogue, in combination with the power spectrum, to measure the matter clustering amplitude S 8 = σ 8 $\sqrt {Ω_{m}/0.3}$. The large-scale structure’s statistical properties are incompletely described by the traditional two-point statistics, motivating our investigation of the PDF—a complementary higher-order statistic. By defining the PDF over the standard-deviation-normalized convergence map, we are able to isolate the non-Gaussian information. We use tailored simulations to compress the data vector and construct a likelihood approximation. We mitigate the impact of survey and astrophysical systematics with cuts on smoothing scales, redshift bins, and data vectors. We find S 8 = $0.860^{+0.066}_{–0.109}$ from the PDF alone and S 8 = 0.798$^{+0.029}_{–0.042}$ from the combination of the PDF and power spectrum (68% confidential level (CL)). The PDF improves the power-spectrum-only constraint by about 10%.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

How decoherence affects the probability of slow-roll eternal inflation

We present that slow-roll inflation can become eternal if the quantum variance of the inflaton field around its slowly rolling classical trajectory is converted into a distribution of classical spacetimes inflating at different rates, and if the variance is large enough compared to the rate of classical rolling that the probability of an increased rate of expansion is sufficiently high. Both of these criteria depend sensitively on whether and how perturbation modes of the inflaton interact and decohere. Decoherence is inevitable as a result of gravitationally sourced interactions whose strength are proportional to the slow-roll parameters. However, the weakness of these interactions means that decoherence is typically delayed until several Hubble times after modes grow beyond the Hubble scale. We present perturbative evidence that decoherence of long-wavelength inflaton modes indeed leads to an ensemble of classical spacetimes with differing cosmological evolutions. We introduce the notion of per-branch observables—expectation values with respect to the different decohered branches of the wave function—and show that the evolution of modes on individual branches varies from branch to branch. Thus, single-field slow-roll inflation fulfills the quantum-mechanical criteria required for the validity of the standard picture of eternal inflation. Finally, for a given potential, the delayed decoherence can lead to slight quantitative adjustments to the regime in which the inflaton undergoes eternal inflation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Generation of arbitrary probability distributions from chaotic dynamics

A framework is developed to derive nonlinear dynamical systems that chaotically generate arbitrary multivariate probability distributions with smooth, deterministic trajectories. Herein, the ideas are used to extend the Nosé-Hoover thermostat methodology to three-dimensional cases where the momentum distribution is nonisotropic and/or non-Gaussian. Toy models that generate several well-known distributions in physics are given as pedagogical examples.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Improved approximations of non-Gaussian probability, force, and energy of a single polymer chain

The mechanical behavior of polymers such as their probability density function (PDF), strain energy, and entropic force, has long been described by the non-Gaussian statistical model. Non-Gaussian models are often approximated by the Kuhn-Grün (KG) distribution function, which is derived from the first-order approximation of the complex Rayleigh's exact Fourier integral distribution. Furthermore, the KG function is widely accepted in polymer physics, where the non-Gaussian theory is often used to describe energy of the chains with various flexibility ratios. However, the KG function is shown to be relevant only for long chains and becomes extremely inaccurate for chains with fewer than 40 segments. In comparison to the KG model, other approximations of the non-Gaussian statistical model are often less accurate, and those with higher accuracy are usually too complex to be implemented in large-scale simulations. Here a new accurate approximation of the non-Gaussian PDF, entropic force, and strain energy of a single chain subsequently is developed to describe the mechanics of a polymer chain. With a similar level of complexity, the presented approximations of non-Gaussian PDF, strain energy, and entropic force are at least 10 times more accurate than KG approximations and thus are an excellent alternative option to be used in micromechanical constitutive models.

42 ENGINEERING↗
DOE OSTI2020

Bypassing the Energy Functional in Density Functional Theory: Direct Calculation of Electronic Energies from Conditional Probability Densities

Density functional calculations can fail for want of an accurate exchange-correlation approximation. The energy can instead be extracted from a sequence of density functional calculations of conditional probabilities (CP DFT). Simple CP approximations yield usefully accurate results for two-electron ions, the hydrogen dimer, and the uniform gas at all temperatures. CP DFT has no self-interaction error for one electron, and correctly dissociates H2, both major challenges. For warm dense matter, classical CP DFT calculations can overcome the convergence problems of Kohn-Sham DFT.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Generalized skew-symmetric interfacial probability distribution in reflectivity and small-angle scattering analysis

Generalized skew-symmetric probability density functions are proposed to model asymmetric interfacial density distributions for the parameterization of any arbitrary density profiles in the `effective-density model'. The penetration of the densities into adjacent layers can be selectively controlled and parameterized. A continuous density profile is generated and discretized into many independent slices of very thin thickness with constant density values and sharp interfaces. The discretized profile can be used to calculate reflectivities via Parratt's recursive formula, or small-angle scattering via the concentric onion model that is also developed in this work.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Narrowing Frequency Probability Density Function for Achieving Minimized Uncertainties in Power Systems Operation – a Stochastic Distribution Control Perspective

With the increased penetration of renewables and other distributed energy resources (DERs), the frequency response in power systems exhibits stochastic nature, where the standard deterministic swing equation should be either represented or transferred into an Ito stochastic differential equation whose solution should be the non-stationary transient behavior of the probability density function (PDF) of the frequency. This transfers the frequency quality control for power systems into a stochastic distribution control problem, where the shape of the frequency distribution, namely the frequency PDF, needs to be directly controlled. In this context, this requires the development of control strategies via controlling the power balance so that the PDF of the frequency is made as narrow as possible whilst centered at its required mean value simple because such a sharp distribution shape means less uncertainties or randomness for the frequency response. In this paper, the formulation of the stochastic swing equation will be made first taking into account of DERs. This will then be followed by the development of stochastic distribution control model that links the power sources with the PDF of the frequency using Fokker Planck Kolmogorov (FPK) equations. A generic constrained optimization problem will be formulated where the cost function is composed of a functional distance between the actual and the desired PDFs of the frequency. A feasible solution using B-spine Neural Networks based stochastic distribution control model will be described. Using the obtained stochastic distribution control model, a set of control algorithms will be described that uses available power sources to shape the PDF of the frequency or to minimize the randomness of the frequency via minimized entropy approach. Future directions will be discussed in the later part of the paper

Swing equation, Power Systems, stchastic distribut↗
DOE OSTI2025

Establishing Models for Digital Twin of Hydropower Systems Using Probability Density Function Shaping

This paper introduces a digital twin modeling method for hydropower systems with Kaplan turbines using probability density function (PDF) shaping. We first use multilayer perceptron (MLP) model to build the discretized openloop Kaplan unit, where the MLP is trained by historical data. Then we use a proportional integral double derivative (PIDD) controller and a lead-lag exciter to test the obtained digital twin model in a closed-loop fashion. Simulation results show that the proposed digital twin modeling method can accurately capture the dynamics of the Kaplan hydropower unit. Finally, we show that the obtained digital twin can help to optimize the PIDD parameters. Compared with the original PIDD controller, the optimized one can achieve an over 90% improvement on the mean square tracking error.

Yin, Zhun [New York University]↗
DOE OSTI2025

Voltage Probability Density Function Shaping Control Strategy Considering Grid Operational Uncertainties

It is well-known that power systems operation always affected by various uncertainties which make the bus voltage a random process that can be characterized by its probability density function (PDF) at any time instant. In this context, this paper presents a novel PDF-based voltage control framework for power systems. By modeling voltage as a stochastic process, we formulate a stochastic differential equationthat captures grid uncertainties. The associated Fokker-Planck-Kolmogorov equation is derived to describe the evolution of the voltage PDF, which enables the formulation of a PDF-shaping control strategy. To simplify the PDF control formulation, a B-spline neural network is introduced for real-time estimation and regulation of the voltage distribution. The proposed PDF control law updates voltage references for energy storage systems and synchronous generators using real-time PDF measurements and feedback signals. The proposed method is validated on a modified Kundur’s two-area system. Simulation results demonstrate that the controller can significantly improve the voltage stability under stochastic conditions, highlighting its effectiveness in modern inverter-rich grids.

Gui, Yonghao [ORNL] (ORCID:0000000250435534)↗
DOE OSTI2016

A validated tumor control probability model based on a meta-analysis of low, intermediate, and high-risk prostate cancer patients treated by photon, proton, or carbon-ion radiotherapy

Purpose: A fully heterogeneous population averaged mechanistic tumor control probability (TCP) model is appropriate for the analysis of external beam radiotherapy (EBRT). This has been accomplished for EBRT photon treatment of intermediate-risk prostate cancer. Extending the TCP model for low and high-risk patients would be beneficial in terms of overall decision making. Furthermore, different radiation treatment modalities such as protons and carbon-ions are becoming increasingly available. Consequently, there is a need for a complete TCP model. Methods: A TCP model was fitted and validated to a primary endpoint of 5-year biological no evidence of disease clinical outcome data obtained from a review of the literature for low, intermediate, and high-risk prostate cancer patients (5218 patients fitted, 1088 patients validated), treated by photons, protons, or carbon-ions. The review followed the preferred reporting item for systematic reviews and meta-analyses statement. Treatment regimens include standard fractionation and hypofractionation treatments. Residual analysis and goodness of fit statistics were applied. Results: The TCP model achieves a good level of fit overall, linear regression results in a p-value of <0.000 01 with an adjusted-weighted-R{sup 2} value of 0.77 and a weighted root mean squared error (wRMSE) of 1.2%, to the fitted clinical outcome data. Validation of the model utilizing three independent datasets obtained from the literature resulted in an adjusted-weighted-R{sup 2} value of 0.78 and a wRMSE of less than 1.8%, to the validation clinical outcome data. The weighted mean absolute residual across the entire dataset is found to be 5.4%. Conclusions: This TCP model fitted and validated to clinical outcome data, appears to be an appropriate model for the inclusion of all clinical prostate cancer risk categories, and allows evaluation of current EBRT modalities with regard to tumor control prediction.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

WE-AB-202-10: Modelling Individual Tumor-Specific Control Probability for Hypoxia in Rectal Cancer

Purpose: To investigate hypoxia-guided dose-boosting for increased tumour control and improved normal tissue sparing using FMISO-PET images Methods: Individual tumor-specific control probability (iTSCP) was calculated using a modified linear-quadratic model with rectal-specific radiosensitivity parameters for three limiting-case assumptions of the hypoxia / FMISO uptake relationship. {sup 18}FMISO-PET images from 2 patients (T3N0M0) from the RHYTHM trial (Investigating Hypoxia in Rectal Tumours NCT02157246) were chosen to delineate a hypoxic region (GTV-MISO defined as tumor-to-muscle ratio > 1.3) within the anatomical GTV. Three VMAT treatment plans were created in Eclipse (Varian): STANDARD (45Gy / 25 fractions to PTV4500); BOOST-GTV (simultaneous integrated boost of 60Gy / 25fr to GTV +0.5cm) and BOOST-MISO (60Gy / 25fr to GTV-MISO+0.5cm). GTV mean dose (in EQD2), iTSCP and normal tissue dose-volume metrics (small bowel, bladder, anus, and femoral heads) were recorded. Results: Patient A showed small hypoxic volume (15.8% of GTV) and Patient B moderate hypoxic volume (40.2% of GTV). Dose escalation to 60Gy was achievable, and doses to femoral heads and small bowel in BOOST plans were comparable to STANDARD plans. For patient A, a reduced maximum bladder dose was observed in BOOST-MISO compared to BOOST-GTV (D0.1cc 49.2Gy vs 54.0Gy). For patient B, a smaller high dose volume was observed for the anus region in BOOST-MISO compared to BOOST-GTV (V55Gy 19.9% vs 100%), which could potentially reduce symptoms of fecal incontinence. For BOOST-MISO, the largest iTSCPs (A: 95.5% / B: 90.0%) assumed local correlation between FMISO uptake and hypoxia, and approached iTSCP values seen for BOOST-GTV (A: 96.1% / B: 90.5%). Conclusion: Hypoxia-guided dose-boosting is predicted to improve local control in rectal tumors when FMISO is spatially correlated to hypoxia, and to reduce dose to organs-at-risk compared to boosting the whole GTV. This could lead to organ-preserving treatment strategies for locally-advanced rectal cancer, thereby improving quality of life. Oxford Cancer Imaging Centre (OCIC); Cancer Research UK (CRUK); Medical Research Council (MRC)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-H-BRA-08: A Monte Carlo Cell Nucleus Model for Assessing Cell Survival Probability Based On Particle Track Structure Analysis

Purpose: To correlate the damage produced by particles of different types and qualities to cell survival on the basis of nanodosimetric analysis and advanced DNA structures in the cell nucleus. Methods: A Monte Carlo code was developed to simulate subnuclear DNA chromatin fibers (CFs) of 30nm utilizing a mean-free-path approach common to radiation transport. The cell nucleus was modeled as a spherical region containing 6000 chromatin-dense domains (CDs) of 400nm diameter, with additional CFs modeled in a sparser interchromatin region. The Geant4-DNA code was utilized to produce a particle track database representing various particles at different energies and dose quantities. These tracks were used to stochastically position the DNA structures based on their mean free path to interaction with CFs. Excitation and ionization events intersecting CFs were analyzed using the DBSCAN clustering algorithm for assessment of the likelihood of producing DSBs. Simulated DSBs were then assessed based on their proximity to one another for a probability of inducing cell death. Results: Variations in energy deposition to chromatin fibers match expectations based on differences in particle track structure. The quality of damage to CFs based on different particle types indicate more severe damage by high-LET radiation than low-LET radiation of identical particles. In addition, the model indicates more severe damage by protons than of alpha particles of same LET, which is consistent with differences in their track structure. Cell survival curves have been produced showing the L-Q behavior of sparsely ionizing radiation. Conclusion: Initial results indicate the feasibility of producing cell survival curves based on the Monte Carlo cell nucleus method. Accurate correlation between simulated DNA damage to cell survival on the basis of nanodosimetric analysis can provide insight into the biological responses to various radiation types. Current efforts are directed at producing cell survival curves for high-LET radiation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-CD-202-10: Tumor Metabolic Control Probability & Dose Response Mapping for Adaptive Dose Painting by Number

Purpose: Adaptive dose-painting-by-number (DPbN) requires a dose-response-mapping (DRM) obtained early in the treatment course. To obtain DRM, voxel-by-voxel tumor dose response needs to be quantified. Our recent study has demonstrated that voxel-by-voxel radio-sensitivity of patient tumor can be determined using tumor-metabolic-ratio measured early during the treatment using FDG-PET images. In this study, the measurements were utilized to construct tumor metabolic control probability (TMCP) and DRM for DPbN. Methods: FDG-PET/CT images of 18 HN cancer patients obtained pre- and weekly during the treatment were used. Spatial parametric images of tumor-metabolic-ratio (dSUV) were constructed following voxel-by-voxel deformable image registration. Each voxel value in dSUV was a function of baseline SUV and delivered dose. Utilizing all values of dSUV in the controlled tumor group at the last treatment week, a cut-off function between the baseline SUV and dSUV was formed, and applied in early treatment days on dSUV of all tumors to model the TMCP. At the treatment week k, TMCP was constructed with respect to the tumor voxel dSUV appeared at the week using the maximum likelihood estimation for all dose levels, and used for DRM construction. Results: TMCPs estimated in the week 2 & 3 have D{sub 50}=11.1∼47.6Gy; γ{sub 50}=0.55∼0.92 respectively with respect to dSUV=0.3∼1.2. The corresponding DRM between tumor voxel dSUV and the expected treatment dose has sigmoid shape. The expected treatment dose are 26∼40Gy (for 95% TMCP) for high sensitive tumor voxels with dSUV=0.3∼0.5; and 65∼110Gy for low sensitive tumor voxels with the dSUV>1.0 depending on the time of the estimation. Conclusion: TMCP can be constructed voxel-by-voxel in human tumor using multiple FDG-PET imaging obtained in early treatment days. TMCP provides a potential quantitative objective of tumor DRM for DPbN to plan the best dose, escalate or de-escalate, in tumor adaptively based on its own radio-sensitivity.

60 APPLIED LIFE SCIENCES↗