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DOE OSTI2024

Analytic Neural Network Gaussian Process Enabled Chance-Constrained Voltage Regulation for Active Distribution Systems with PVs, Batteries and EVs

This paper proposes an analytic neural network Gaussian process (NNGP)-based chance-constrained real-time voltage regulation method for active distribution systems with photovoltaics (PVs), batteries, and electric vehicles (EVs). NNGP can utilize historical measurement data to achieve real-time probabilistic node voltage estimation through Bayesian inference. Then, NNGP is fully analytically embedded into the optimal power flow model to perform voltage regulation and adapt to various topological changes. The uncertainties of voltage estimations are easily considered via the chance constraint, and it has been shown that the adoption of this chance constraint can significantly improve the reliability of voltage regulation under various scenarios. The comparison results with other methods, carried out on a real 759-node distribution system located in western Colorado, U.S., show that the proposed method can achieve accurate voltage estimation across different topologies and reliably perform voltage regulation considering PVs, batteries, and EVs.

active distribution systems↗

DOE OSTI2018

Towards Malware Detection via CPU Power Consumption: Data Collection Design and Analytics

This paper presents an experimental design and data analytics approach aimed at power-based malware detection on general-purpose computers. Leveraging the fact that malware executions must consume power, we explore the postulate that malware can be accurately detected via power data analytics. Our experimental design and implementation allow for programmatic collection of CPU power profiles for fixed tasks during uninfected and infected states using five different rootkits. To characterize the power consumption profiles, we use both simple statistical and novel, sophisticated features. We test a one-class anomaly detection ensemble (that baselines non-infected power profiles) and several kernel-based SVM classifiers (that train on both uninfected and infected profiles) in detecting previously unseen malware and clean profiles. The anomaly detection system exhibits perfect detection when using all features and tasks, with smaller false detection rate than the supervised classifiers. The primary contribution is the proof of concept that baselining power of fixed tasks can provide accurate detection of rootkits. Moreover, our treatment presents engineering hurdles needed for experimentation and allows analysis of each statistical feature individually. This work appears to be the first step towards a viable power-based detection capability for general-purpose computers, and presents next steps toward this goal.

Bridges, Robert↗

DOE OSTI2023

Analytical Large-Signal Modeling of Inverter-Based Microgrids With Koopman Operator Theory for Autonomous Control

The microgrid (MG) plays a crucial role in the energy transition, but its nonlinearity presents a significant challenge for large-signal power systems studies in the electromagnetic transient (EMT) time scale. In this paper, we develop a large-signal linear MG model that considers the detailed dynamics of the primary and zero-control levels based on the Koopman operator (KO) theory. Firstly, a set of observable functions is carefully designed to capture the nonlinear dynamics of the MG. The corresponding linear KO is then analytically derived based on these observables, resulting in the linear representation of the original nonlinear MG with observables as the new coordinate. The influence of external input on the system dynamics is also considered during the derivation, enabling control of the MG. We solve the voltage control problem using the traditional linear quadratic integrator (LQI) method to demonstrate that textbook linear control techniques can accurately control the original nonlinear MG via the developed KO-linearized MG model. Our proposed KO linearization method is generic and can be easily extended for different control objectives and MG structures using our analytical derivation procedure. Here, we validate the effectiveness of our methodology through various case studies.

25 ENERGY STORAGE↗

DOE OSTI2020

Towards Interactive, Reproducible Analytics at Scale on HPC Systems

The growth in scientific data volumes has resulted in a need to scale up processing and analysis pipelines using High Performance Computing (HPC) systems. These workflows need interactive, reproducible analytics at scale. The Jupyter platform provides core capabilities for interactivity but was not designed for HPC systems. In this paper, we outline our efforts that bring together core technologies based on the Jupyter Platform to create interactive, reproducible analytics at scale on HPC systems. Our work is grounded in a real world science use case-applying geophysical simulations and inversions for imaging the subsurface. Our core platform addresses three key areas of the scientific analysis workflow-reproducibility, scalability, and interactivity. We describe our implemention of a system, using Binder, Science Capsule, and Dask software. We demonstrate the use of this software to run our use case and interactively visualize real-Time streams of HDF5 data.

containers↗

DOE OSTI2016

Changes in geophysical properties caused by fluid injection into porous rocks: analytical models: Geophysical changes in porous rocks

Analytical models are provided that describe how the elastic compliance, electrical conductivity, and fluid-flow permeability of rocks depend on stress and fluid pressure. In order to explain published laboratory data on how seismic velocities and electrical conductivity vary in sandstones and granites, the models require a population of cracks to be present in a possibly porous host phase. The central objective is to obtain a consistent mean-field analytical model that shows how each modeled rock property depends on the nature of the crack population. We describe the crack populations by a crack density, a probability distribution for the crack apertures and radii, and the averaged orientation of the cracks. The possibly anisotropic nature of the elasticity, conductivity, and permeability tensors is allowed for; however, only the isotropic limit is used when comparing to laboratory data. For the transport properties of conductivity and permeability, the percolation effect of the crack population linking up to form a connected path across a sample is modeled. But, this effect is important only in crystalline rock where the host phase has very small conductivity and permeability. In general, the importance of the crack population to the transport properties increases as the host phase becomes less conductive and less permeable.

58 GEOSCIENCES↗

DOE OSTI2026

A Scoping Review of Mixed Initiative Visual Analytics in the Automation Renaissance

Artificial agents are increasingly integrated into data analysis workflows, carrying out tasks that were primarily done by humans. Our research explores how the introduction of automation recalibrates the dynamic between humans and automating technology. To explore this question, we conducted a scoping review encompassing twenty years of mixed-initiative visual analytic systems. To describe and contrast the relationship between humans and automation, we developed an integrated taxonomy to delineate the objectives of these mixed-initiative visual analytics tools, how much automation they support, and the assumed roles of humans. Here, we describe our qualitative approach of integrating existing theoretical frameworks with new codes we developed. Our analysis shows that the visualization research literature lacks consensus on the definition of mixed-initiative systems and explores a limited potential of the collaborative interaction landscape between people and automation. Our research provides a scaffold to advance the discussion of human-AI collaboration during visual data analysis. Our integrated taxonomy is available in the form of a web application on https://smonadjemi.github.io/miva.

Monadjemi, Shayan [ORNL] (ORCID:0000000293855969)↗

DOE OSTI2024

Semi–Analytical Modeling of Transient Stream Drawdown and Depletion in Response to Aquifer Pumping

Analytical and semi–analytical models for stream depletion with transient stream stage drawdown induced by groundwater pumping are developed to address a deficiency in existing models, namely, the use of a fixed stream stage condition at the stream–aquifer interface. Here field data are presented to demonstrate that stream stage drawdown does indeed occur in response to groundwater pumping near aquifer–connected streams. A model that predicts stream depletion with transient stream drawdown is developed based on stream channel mass conservation and finite stream channel storage. The resulting models are shown to reduce to existing fixed–stage models in the limit as stream channel storage becomes infinitely large, and to the confined aquifer flow with a no–flow boundary at the streambed in the limit as stream storage becomes vanishingly small. The model is applied to field measurements of aquifer and stream drawdown, giving estimates of aquifer hydraulic parameters, streambed conductance, and a measure of stream channel storage. The results of the modeling and data analysis presented herein have implications for sustainable groundwater management.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Boron Coordination in Multicomponent Glasses: Analytical Models and Machine Learning With Uncertainty

Borosilicate glasses are extensively used in a variety of applications from kitchenware to nuclear waste immobilization due to the strong network formed by the Si-O-B bond that makes it resistant to chemical corrosion and gives it a low thermal expansion. Boron, however, exists in both trigonal BO3 and tetrahedral BO4 bonds in glass systems, which impacts the chemical durability and thermal resistance of the glass, amongst other properties. Boron coordination (N4), or the ratio of the amount of BO4 to BO3 within a glass, may aid in predicting these properties but is difficult to derive without experimental data due to the complexity of impacts from varied glass compositions and processing factors. For this reason, compositional models have been developed to predict boron coordination, but the models typically include a limited number of glass components. To help fill this gap in the models, in this work, a diverse multicomponent glass dataset of 809 glasses is compiled from a literature search, and then a number of analytical and machine learning (ML) models are trained on the dataset. Previously developed modified Bernstein and modified Du Stebbins analytical models were fitted to update parameters with the new dataset. Then, partially Bayesian neural networks, Gaussian process regressor, and heteroskedastic deterministic neural networks were evaluated. The ML models examined all have different strategies to overcome the potential for overfitting as a result of a limited training dataset, and return results that account for model uncertainty, which can be valuable for understanding model reliability. For the first time, cooling rate is introduced as an input parameter for ML models, showing consistent improvements in performance and solidifying the importance of including parameters outside of composition alone for N4 prediction. The machine learning models examined here show promise in accurate predictions of boron coordination in borosilicate glasses, all achieving R2 values of 0.91.

boron coordination↗

DOE OSTI2020

Analytical Study to Use the Excess Digester Gas of Wastewater Treatment Plants

This study presents an analytical method that can be used to enhance the power production rate and the energy-saving at wastewater treatment plants. The digester used at wastewater treatment plants produces digester gas by anaerobic digestion, with which biofuel production can be achieved. Biofuels can be used to meet some of the energy requirements of the wastewater treatment facility through combined heat and power (CHP) gas engines (cogeneration). Using micro gas turbine (MGT), a CHP technology can be introduced in wastewater treatment plants (WWTPs). The combination of MGTs and absorption chillers is a promising technology as it produces electricity, heating, and cooling simultaneously. The study demonstrated how the waste heat of MGTs could be used to drive absorption chillers. In this analytical study, a detailed technical and economic analysis is provided on the trigeneration system, i.e., the integration of MGTs and absorption chillers driven by waste digester gas of the wastewater treatment plants. It can meet the heating and cooling demands of the plants, which promote the reduction of utility costs. The technology presented is also useful for other thermal energy users.

09 BIOMASS FUELS↗

DOE OSTI2015

Improving Wind Turbine Drivetrain Reliability Using a Combined Experimental, Computational, and Analytical Approach

Nontorque loads induced by the wind turbine rotor overhang weight and aerodynamic forces can greatly affect drivetrain loads and responses. If not addressed properly, these loads can result in a decrease in gearbox component life. This work uses analytical modeling, computational modeling, and experimental data to evaluate a unique drivetrain design that minimizes the effects of nontorque loads on gearbox reliability: the Pure Torque(R) drivetrain developed by Alstom. The drivetrain has a hub-support configuration that transmits nontorque loads directly into the tower rather than through the gearbox as in other design approaches. An analytical model of Alstom's Pure Torque drivetrain provides insight into the relationships among turbine component weights, aerodynamic forces, and the resulting drivetrain loads. Main shaft bending loads are orders of magnitude lower than the rated torque and are hardly affected by wind conditions and turbine operations.

17 WIND ENERGY↗

DOE OSTI2020

Modeling thin layers of analytes on substrates for spectral analysis: use of solid/liquid n and k values to model reflectance spectra

Since solids are only sometimes seen en masse in a pure bulk form, and for liquids other than water almost never, a capability to model reflectance spectra from analytes deposited on various substrates would be highly advantageous. If available, the real, n ( ν ) , and imaginary, k ( ν ) , components of the complex refractive index, n n + i k , can be used to simulate infrared spectra, accounting for reflection, refraction, and absorption phenomena as a function of wavelength. We focus on using the Pacific Northwest National Laboratory (PNNL) derived n / k vectors for solid and liquid analytes deposited as thin layers on different types of substrates including conductors, such as aluminum, and inorganic dielectrics, such as glass. The model is an adaptation of the Monte Carlo ray trace modeling program, TracePro, extended through the use of its macrolanguage. The model is tested using thin films of organic liquids including silicone oil and no. 2 diesel fuel, as well as organic solids such as caffeine and acetaminophen on aluminum and glass. The predicted spectra for the solid films were compared to experimental hemispherical reflectance data measured using a Fourier transform spectrometer with an integrating sphere. The thickness of the calculated layer is a parameter for predicting the (transflectance) spectra and is obtained using the areal density measured from gravimetric methods to generate the thin-layer samples. Comparison of the calculated spectra with experimental hemispherical reflectance data shows excellent agreement, indicating promise for the use of measured n / k data to synthesize reference spectral data. In particular, accounting for the inhomogeneity of the deposits greatly improved the match with experimental data. Finally, the theoretical modeling shows that for thicker layers (ca. 20 to 100 μm) of typical organics possessing moderately strong k values, the longwave infrared features are often saturated and better spectral contrast is obtained from the overtone/combination bands in the shortwave infrared.

42 ENGINEERING↗

DOE OSTI2020

Analytical expressions of the surface shape of ‘diaboloid’ mirrors

Modern deterministic polishing processes allow fabrication of x-ray optics with almost any arbitrary aspherical surface shape. Among these optics, the so called "diaboloid"mirror is of special interest. The diaboloid mirror that converts a cylindrical wave to a spherical wave would improve focusing in x-ray beamlines implementing a diffraction element between a parabolic cylinder and a toroidal mirror. The replacement of the toroidal mirror in existing beamlines by the diaboloid mirror would mitigate aberrations. The shape of the diaboloid mirror is usually calculated numerically based on a truncated polynomial solution of the optical path problem. Here, we present an exact analytical solution for the shape of a diaboloid mirror as a function of the conjugate parameters of the mirror placed in a beamline. The derived analytical expressions for the diaboloid mirror in both the canonical and mirror-based coordinate systems are implemented in ray-tracing simulations to verify the beamline performances.

Yashchuk, Valeriy V.↗

DOE OSTI2023

Generalized analytical and numerical modeling of optical second harmonic generation in anisotropic crystals and complex heterostructures using #SHAARP package

Optical second harmonic generation (SHG) is a nonlinear optical effect widely used for nonlinear optical microscopy and laser frequency conversion. The closed-form analytical solution of the nonlinear optical responses is essential for evaluating the optical responses of new materials whose optical properties are unknown a priori. Many approximations have therefore been employed in the existing analytical approaches, such as slowly varying approximation, weak reflection of the nonlinear polarization, transparent medium, high crystallographic symmetry, Kleinman symmetry, easy crystal orientation along a high-symmetry direction, phase matching conditions and negligible interference among nonlinear waves, which may lead to large errors in the reported material properties. To avoid these approximations, here we have developed an open-source package named Second Harmonic Analysis of Anisotropic Rotational Polarimetry (#SHAARP) for single interface (si) and in multilayers (ml) for homogeneous crystals. The reliability and accuracy are established by experimentally benchmarking with both the SHG polarimetry and Maker fringes predicted from the package using standard materials. SHAARP.si and SHAARP.ml are available through GitHub https://github.com/Rui-Zu/SHAARP and https://github.com/bzw133/SHAARP.ml, respectively.

complex systems↗

DOE OSTI2014

SU-E-I-01: A Fast, Analytical Pencil Beam Based Method for First Order X-Ray Scatter Estimation of Kilovoltage Cone Beam X-Rays

Purpose: To analytically estimate first-order x-ray scatter for kV cone beam x-ray imaging with high computational efficiency. Methods: In calculating first-order scatter using the Klein-Nishina formula, we found that by integrating the point-to-point scatter along an interaction line, a “pencil-beam” scatter kernel (BSK) can be approximated to a quartic expression when the imaging field is small. This BSK model for monoenergetic, 100keV x-rays has been verified on homogeneous cube and cylinder water phantoms by comparing with the exact implementation of KN formula. For heterogeneous medium, the water-equivalent length of a BSK was acquired with an improved Siddon's ray-tracing algorithm, which was also used in calculating pre- and post- scattering attenuation. To include the electron binding effect for scattering of low-kV photons, the mean corresponding scattering angle is determined from the effective point of scattered photons of a BSK. The behavior of polyenergetic x-rays was also investigated for 120kV x-rays incident to a sandwiched infinite heterogeneous slab phantom, with the electron binding effect incorporated. Exact computation and Monte Carlo simulations were performed for comparisons, using the EGSnrc code package. Results: By reducing the 3D volumetric target (o(n{sup 3})) to 2D pencil-beams (o(n{sup 2})), the computation expense can be generally lowered by n times, which our experience verifies. The scatter distribution on a flat detector shows high agreement between the analytic BSK model and exact calculations. The pixel-to-pixel differences are within (-2%, 2%) for the homogeneous cube and cylinder phantoms and within (0, 6%) for the heterogeneous slab phantom. However, the Monte Carlo simulation shows increased deviation of the BSK model toward detector periphery. Conclusion: The proposed BSK model, accommodating polyenergetic x-rays and electron binding effect at low kV, shows great potential in efficiently estimating the first-order scatter from small imaging fields. We are investigating more thoroughly to improve performance and explore applications.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2014

TH-C-19A-01: Analytic Design Method to Make a 2D Planar, Segmented Ion Chamber Water-Equivalent for Proton Dose Measurements

Purpose: Quality Assurance (QA) measurements of proton therapy fields must accurately measure steep longitudinal dose gradients as well as characterize the dose distribution laterally. Currently, available devices for two-dimensional field measurements perturb the dose distribution such that routine QA measurements performed at multiple depths require multiple field deliveries and are time consuming. Methods: A design procedure for a two-dimensional detector array is introduced whereby the proton energy loss and scatter are adjusted so that the downstream dose distribution is maintained to be equivalent to that which would occur in uniform water. Starting with the design for an existing, functional two-dimensional segmented ion chamber prototype, a compensating material is introduced downstream of the detector to simultaneously equate the energy loss and lateral scatter in the detector assembly to the values in water. An analytic formalism and procedure is demonstrated to calculate the properties of the compensating material in the general case of multiple layers of arbitrary material. The resulting design is validated with Monte Carlo simulations. Results: With respect to the specific prototype design considered, the results indicate that a graphite compensating layer of the proper dimensions can yield proton beam range perturbation less than 0.1mm and beam sigma perturbation less than 2% across the energy range of therapeutic proton beams. Conclusion: We have shown that, for a 2D gas-filled detector array, a graphite-compensating layer can balance the energy loss and multiple Coulomb scattering relative to uniform water. We have demonstrated an analytic formalism and procedure to determine a compensating material in the general case of multiple layers of arbitrary material. This work was supported by the US Army Medical Research and Materiel Command under Contract Agreement No. DAMD17-W81XWH-04-2-0022. Opinions, interpretations, conclusions and recommendations are those of the author and are not necessarily endorsed by the US Army.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2014

TH-C-BRD-02: Analytical Modeling and Dose Calculation Method for Asymmetric Proton Pencil Beams

Purpose: A dynamic collimation system (DCS), which consists of two pairs of orthogonal trimmer blades driven by linear motors has been proposed to decrease the lateral penumbra in pencil beam scanning proton therapy. The DCS reduces lateral penumbra by intercepting the proton pencil beam near the lateral boundary of the target in the beam's eye view. The resultant trimmed pencil beams are asymmetric and laterally shifted, and therefore existing pencil beam dose calculation algorithms are not capable of trimmed beam dose calculations. This work develops a method to model and compute dose from trimmed pencil beams when using the DCS. Methods: MCNPX simulations were used to determine the dose distributions expected from various trimmer configurations using the DCS. Using these data, the lateral distribution for individual beamlets was modeled with a 2D asymmetric Gaussian function. The integral depth dose (IDD) of each configuration was also modeled by combining the IDD of an untrimmed pencil beam with a linear correction factor. The convolution of these two terms, along with the Highland approximation to account for lateral growth of the beam along the depth direction, allows a trimmed pencil beam dose distribution to be analytically generated. The algorithm was validated by computing dose for a single energy layer 5×5 cm{sup 2} treatment field, defined by the trimmers, using both the proposed method and MCNPX beamlets. Results: The Gaussian modeled asymmetric lateral profiles along the principal axes match the MCNPX data very well (R{sup 2}≥0.95 at the depth of the Bragg peak). For the 5×5 cm{sup 2} treatment plan created with both the modeled and MCNPX pencil beams, the passing rate of the 3D gamma test was 98% using a standard threshold of 3%/3 mm. Conclusion: An analytical method capable of accurately computing asymmetric pencil beam dose when using the DCS has been developed.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2015

SU-E-T-120: Analytic Dose Verification for Patient-Specific Proton Pencil Beam Scanning Plans

Purpose: To independently verify the QA dose of proton pencil beam scanning (PBS) plans using an analytic dose calculation model. Methods: An independent proton dose calculation engine is created using the same commissioning measurements as those employed to build our commercially available treatment planning system (TPS). Each proton PBS plan is exported from the TPS in DICOM format and calculated by this independent dose engine in a standard 40 x 40 x 40 cm water tank. This three-dimensional dose grid is then compared with the QA dose calculated by the commercial TPS, using standard Gamma criterion. A total of 18 measured pristine Bragg peaks, ranging from 100 to 226 MeV, are used in the model. Intermediate proton energies are interpolated. Similarly, optical properties of the spots are measured in air over 15 cm upstream and downstream, and fitted to a second-order polynomial. Multiple Coulomb scattering in water is approximated analytically using Preston and Kohler formula for faster calculation. The effect of range shifters on spot size is modeled with generalized Highland formula. Note that the above formulation approximates multiple Coulomb scattering in water and we therefore chose not use the full Moliere/Hanson form. Results: Initial examination of 3 patient-specific prostate PBS plans shows that agreement exists between 3D dose distributions calculated by the TPS and the independent proton PBS dose calculation engine. Both calculated dose distributions are compared with actual measurements at three different depths per beam and good agreements are again observed. Conclusion: Results here showed that 3D dose distributions calculated by this independent proton PBS dose engine are in good agreement with both TPS calculations and actual measurements. This tool can potentially be used to reduce the amount of different measurement depths required for patient-specific proton PBS QA.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-142: An Analytical Model to Correct the Aperture Scattered Dose in Clinical Proton Beams

Purpose: Apertures or collimators are used to laterally shape proton beams in double scattering (DS) delivery and to sharpen the penumbra in pencil beam (PB) delivery. However, aperture-scattered dose is not included in the current dose calculations of treatment planning system (TPS). The purpose of this study is to provide a method to correct the aperture-scattered dose based on an analytical model. Methods: A DS beam with a non-divergent aperture was delivered using a single-room proton machine. Dose profiles were measured with an ion-chamber scanning in water and a 2-D ion chamber matrix with solid-water buildup at various depths. The measured doses were considered as the sum of the non-contaminated dose and the aperture-scattered dose. The non-contaminated dose was calculated by TPS and subtracted from the measured dose. Aperture scattered-dose was modeled as a 1D Gaussian distribution. For 2-D fields, to calculate the scatter-dose from all the edges of aperture, a sum of weighted distance was used in the model based on the distance from calculation point to aperture edge. The gamma index was calculated between the measured and calculated dose with and without scatter correction. Results: For a beam with range of 23 cm and aperture size of 20 cm, the contribution of the scatter horn was ∼8% of the total dose at 4 cm depth and diminished to 0 at 15 cm depth. The amplitude of scatter-dose decreased linearly with the depth increase. The 1D gamma index (2%/2 mm) between the calculated and measured profiles increased from 63% to 98% for 4 cm depth and from 83% to 98% at 13 cm depth. The 2D gamma index (2%/2 mm) at 4 cm depth has improved from 78% to 94%. Conclusion: Using the simple analytical method the discrepancy between the measured and calculated dose has significantly improved.

60 APPLIED LIFE SCIENCES↗