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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Shifting Left for Machine Learning: An Empirical Study of Security Weaknesses in Supervised Learning-based Projects

Context: Supervised learning-based projects (SLPs), i.e., software projects that use supervised learning algorithms, such as decision trees are useful for performing classification-related tasks. Yet, security weaknesses, such as the use of hard-coded passwords in SLPs, can make SLPs susceptible to security attacks. A characterization of security weaknesses in SLPs can help practitioners understand the security weaknesses that are frequent in SLPs and adopt adequate mitigation strategies. Objective: The goal of this paper is to help practitioners se-curely develop supervised learning-based projects by conducting an empirical study of security weaknesses in supervised learning-based projects. Methodology: We conduct an empirical study by quantifying the frequency of security weaknesses in 278 open source SLPs. Results: We identify 22 types of security weaknesses that occur in SLPs. We observe ‘use of potentially dangerous function’ to be the most frequently occurring security weakness in SLPs. Of the identified 3,964 security weaknesses, 23.79 % and 40.49 % respectively, appear for source code files used to train and test models. We also observe evidence of co-location, e.g., instances of command injection co-locates with instances of potentially dangerous function. Conclusion: Based on our findings, we advocate for a shift left approach for SLP development with security-focused code reviews, and application of security static analysis.

Bhuiyan, Farzana Ahamed↗

DOE OSTI2020

Minimum Detectable Quantity Calculation for Radiation Portal Monitors

The minimum detectable quantity of a radiation portal monitor is the smallest amount of radioactive material that can be detected passing through the monitor (with a specified detection probability). The minimum detectable quantity is a function of many factors, including isotope, velocity, distance between pillars, height of portal and vehicle, source distribution and position, background radiation, background suppression, detector volume and positions, detector efficiency, decision metrics and algorithms, the presence of NORM (naturally occurring radioactive material), and alarm thresholds. Experimentally testing a radiation portal monitor to failure for all combinations of these factors is extremely time-consuming and often cost prohibitive. This document outlines a straightforward method for quickly estimating the minimum detectable quantity for moving sources over a large variety of conditions with a minimal number of static measurements. The document also describes a proof of concept software application that the International Atomic Energy Agency has designed based on the described method that can be used by Member States to estimate a monitor’s minimum detectable quantity.

Blessinger, Christopher S.↗

DOE OSTI2022

Thermite and intermetallic projectiles examined experimentally in air and inert gas environments

Intermetallic (aluminum and zirconium) and thermite (aluminum and molybdenum trioxide) projectiles were launched using a high velocity impact ignition testing system. The experiments were designed to simulate reactivity in high (argon) and low (air) altitude environments. The projectiles were launched into a chamber that included a steel target plate for projectile penetration before impacting a rear witness plate. The chamber was semi-sealed and instrumented for quasi-static pressure data. The results provide an understanding of energy release from the projectile materials and of the environmental influence on performance. The transient pressure traces provide insight into reaction kinetics. A bifurcation in transient pressure rise was an indication of a shift in reaction kinetics from the inherent reactive material to metal oxidation with the environment. The bifurcation was delayed by about 0.15 ms for the intermetallic relative to the thermite, evidence that the thermite reaction proceeded faster upon impact than the intermetallic. The two-step process (impact ignition of the reactive material followed by metal oxidation) was shown to produce higher energy conversion efficiencies than projectiles composed of pure fuel (i.e., aluminum) reported previously. Both reactive materials showed energy conversion efficiencies greater than 30% (for air) and 50% (for argon), and an explanation of underestimated efficiency and energy losses is provided. These results have implications for advancing formulations for ballistic applications. Structural reactive materials can be used to modify the effective reactivity of metal-containing formulations in varied atmospheric environments.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Improving the nonlinear control performance of the supply fan at air handling units using a gain scheduling control strategy

Due to its nonlinear nature, the supply fan at air handling units with the controller tuned at the design condition tends to be aggressive and oscillate under partial load conditions. Here, the objective of this paper is to develop and validate a gain scheduling control strategy to improve its nonlinear control performance. First, a control-oriented model, which does not require numerous physical parameters and extensive test data, is developed to study the nonlinearity of the fan system. Based on the theoretical model and experimental verifications, the issue of an aggressive response with a conventional fixed-gain controller is caused by the fact that the system gain is proportional to the ratio of the duct static pressure to the fan speed. To address the issue, a scheduling function of the measurable duct static pressure and fan speed is proposed to be included in the conventional fixed-gain controller to compensate for the fan system gain variation. The gain scheduling control strategy is found to approximately maintain the identical control performance under all operation conditions. Most importantly, the gain scheduling control strategy can be readily implemented without intensive computation and additional measurements, showing a promising potential in industrial applications.

42 ENGINEERING↗

DOE OSTI2021

Drift orbit islands of energetic particles due to 3D fields in ITER

In this study, we report a comparative study of the orbit islands formed by the guiding center drift motion of test energetic particles (EPs), including both high-energy deuterium ions and fusion-born α-particles, with respect to the magnetic islands formed by tracing the field lines, for an ITER plasma representing the 15 MA baseline scenario. The particle drift orbit is modified by the presence of static resonant magnetic perturbations (RMPs) of different toroidal mode numbers n (n = 1 and 3 in this study), forming orbit islands in the Poincaré plane by passing EPs. The key findings are as follows. (i) With an n = 1 RMP field, the size of the orbit islands combined with the total RMP field, including the plasma response, is about three times smaller than that obtained by assuming the corresponding vacuum field. (ii) The orbit island size is not sensitive to the EP energy, and is comparable to those of the magnetic islands. (iii) Passing EPs with outward radial orbital drift form orbit islands that shift inward with respect to the corresponding magnetic islands, and vice versa. This radial shift, ΔΨ, measured in the normalized equilibrium poloidal flux, is quantified as ΔΨ ≃ 0.03X for the ITER baseline plasma and assuming n = 1 RMPs, with $X\equiv {(M/{M}_{\mathrm{p}})}^{1/2}{(E[\mathrm{M}\mathrm{e}\mathrm{V}])}^{1/2}{Z}^{-1}$, where M is the particle mass, Mp is the proton mass, E is the particle energy, and Z is the particle charge number. (iv) Trapped EPs do not form drift orbit islands, even in the presence of the 3D fields produced by the 90 kAt ELM control coil current in ITER, and thus possess good confinement properties. Nevertheless, the deformation of the trapped particle drift orbits in the Poincaré plane shows that the canonical toroidal angular momentum of EPs is no longer conserved in the presence of the RMP fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Toward Automated Detection of Portability Bugs in Kokkos Parallel Programs

Performance-portable programming frameworks provide abstractions for parallel execution to allow easily porting an application to multiple backend programming models, such as CUDA, HIP, and OpenMP. However, programs may still have portability bugs that manifest only on specific backends. Traditional testing is ineffective in discovering these bugs, as it would require concrete execution on all supported hardware configurations for a potentially infinite set of inputs. To mitigate this issue, we focused on a specific programming framework, Kokkos, and identified several categories of common portability bugs. We then developed Klokkos, a static analysis approach based on symbolic execution that can run on commodity hardware, before execution on supercomputers. As a proof-of-concept, we ran Klokkos on examples encoding the identified bugs. Our results show that Klokkos is effective, efficient, and precise: it detected all the considered bugs, quickly, and without any false positives. Although preliminary, our results motivate further research and development in this direction.

Kale, Vivek↗

DOE OSTI2023

Prediction of chronic kidney disease progression using recurrent neural network and electronic health records

Chronic kidney disease (CKD) is a progressive loss in kidney function. Early detection of patients who will progress to late-stage CKD is of paramount importance for patient care. To address this, we develop a pipeline to process longitudinal electronic heath records (EHRs) and construct recurrent neural network (RNN) models to predict CKD progression from stages II/III to stages IV/V. The RNN model generates predictions based on time-series records of patients, including repeated lab tests and other clinical variables. Our investigation reveals that using a single variable, the recorded estimated glomerular filtration rate (eGFR) over time, the RNN model achieves an average area under the receiver operating characteristic curve (AUROC) of 0.957 for predicting future CKD progression. When additional clinical variables, such as demographics, vital information, lab test results, and health behaviors, are incorporated, the average AUROC increases to 0.967. In both scenarios, the standard deviation of the AUROC across cross-validation trials is less than 0.01, indicating a stable and high prediction accuracy. Our analysis results demonstrate the proposed RNN model outperforms existing standard approaches, including static and dynamic Cox proportional hazards models, random forest, and LightGBM. The utilization of the RNN model and the time-series data of previous eGFR measurements underscores its potential as a straightforward and effective tool for assessing the clinical risk of CKD patients concerning their disease progression.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Hybrid Solid Oxide Fuel Cell/Gas Turbine Model Development for Electric Aviation

A thermodynamic model was developed and validated to analyze a high-performance solid oxide fuel cell and gas turbine (SOFC-GT) hybrid power system for electric aviation. This study used a process simulation software package (ProMax) to study the role of SOFC design and operation on the feasibility and performance of the hybrid system. Standard modules, including compressor, turbine, heat exchanger, reforming reactor, and combustor were used from the ProMax tool suite while a custom module was created to simulate the SOFC stack. The model used an SOFC test data set as an input. Additional SOFC stack performance effects, such as pressure, temperature, and utilization of air and fuel, were added from open source data. System performance predictors were SOFC specific power, fuel-to-electricity conversion efficiency, and hybrid system efficiency. Using these input data and predictors, a static thermodynamic performance model was created that can be modified for different system configurations and operating conditions. Prior to creating the final aircraft performance model, initial demonstration models were developed to validate output results. We used the NASA SOFC model as a benchmark, which was created with their Numerical Propulsion System Simulator (NPSS) software framework. Our output results matched within 1% of both the NASA model and open source SOFC performance data. With confidence gained in the accuracy of this model, a 1-MW SOFC-GT hybrid power system was constructed for an aircraft propulsion concept. Overall hybrid system efficiencies of > 75% FTE were observed during standard 36,000 feet cruise flight conditions.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2023

Comparative verification of hydro-mechanical fracture behavior: Task G of international research project DECOVALEX–2023

Numerical simulations become a necessity when experimental approaches cannot cover the required physical and time scale of interest. One of such area is a simulation of long-term host rock behaviors for nuclear waste disposal and simulation tools involved in the assessment must go through rigorous validation tests. The DECOVALEX project (Development of COupled models and their VAlidation against EXperiments) is dedicated to this purpose by international participants. This work is part of the ongoing phase DECOVALEX–2023 (D–2023, Task G) particularly aiming to simulate fracture behaviors under various conditions. Here, in this study, we cross-verified a variety of numerical methods including continuous and discontinuous approaches against four benchmark exercises with emphasis on numerical accuracy and parameterization of the various numerical approaches. The systematic inter-comparisons of test cases highlight advantages and disadvantages of the different numerical models. Numerical details on discretization effects (e.g. mesh density and orientation) and domain size were investigated in detail for practical applications. It became evident that meticulous attention to mesh resolution and domain size is imperative for achieving accurate numerical simulations, even for static cracks. Moreover, when comparing numerical methods to closed-form solutions for static cracks, all models successfully reproduced the maximum crack opening but encountered challenges near the crack tips. Finally, the paper discusses how to convert between and therefore compare parameters of various numerical approaches. Our benchmark studies reveal that each model necessitates a distinct number of parameters, even in simple scenarios like static crack aperture benchmarks. It is generally more practical to employ fewer parameters to mitigate model over-parameterization and enhance experimental feasibility.

58 GEOSCIENCES↗

DOE OSTI2022

Survival analysis of localized prostate cancer with deep learning

In recent years, data-driven, deep-learning-based models have shown great promise in medical risk prediction. By utilizing the large-scale Electronic Health Record data found in the U.S. Department of Veterans Affairs, the largest integrated healthcare system in the United States, we have developed an automated, personalized risk prediction model to support the clinical decision-making process for localized prostate cancer patients. This method combines the representative power of deep learning and the analytical interpretability of parametric regression models and can implement both time-dependent and static input data. To collect a comprehensive evaluation of model performances, we calculate time-dependent C-statistics C td over 2-, 5-, and 10-year time horizons using either a composite outcome or prostate cancer mortality as the target event. The composite outcome combines the Prostate-Specific Antigen (PSA) test, metastasis, and prostate cancer mortality. Our longitudinal model Recurrent Deep Survival Machine (RDSM) achieved C td 0.85 (0.83), 0.80 (0.83), and 0.76 (0.81), while the cross-sectional model Deep Survival Machine (DSM) attained C td 0.85 (0.82), 0.80 (0.82), and 0.76 (0.79) for the 2-, 5-, and 10-year composite (mortality) outcomes, respectively. In addition to estimating the survival probability, our method can quantify the uncertainty associated with the prediction. The uncertainty scores show a consistent correlation with the prediction accuracy. We find PSA and prostate cancer stage information are the most important indicators in risk prediction. Our work demonstrates the utility of the data-driven machine learning model in prostate cancer risk prediction, which can play a critical role in the clinical decision system.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Metal-to-Ceramic Joining Methods to Support Development of Advanced Ceramic-Based CSP Components

The National Renewable Energy Laboratory, Missouri University of Science and Technology (MS&T), Massachusetts Institute of Technology (MIT), and Colorado School of Mines (CSM) collaborated to design, develop, and test a material concept at bench scale which will be used to achieve a ceramic-to-metal (C2M) joint between a selected metal HTF loop material and a selected ceramic material used by the Gen3 CSP technology pathway. The final joint assembly will need to possess sufficient mechanical properties to withstand static high-temperature (650 degrees-700 degrees C) and high-pressure (20 MPa) and thermal cycling (between 650 degrees C and 100 degrees C) conditions. The material concept consists of three key components: (1) a ceramic matrix composite (CMC) that serves as a compliant transition material aiming to mitigate the stresses due to the mismatch of coefficient of thermal expansion (CTE) from a direct ceramic-to-metal joint, (2) a metal-end joint utilizing a multi-principal element alloy (MPEA) with changing percentage of particle loading to bond the candidate metal to the CMC, and (3) a ceramic-end joint utilizing a glass ceramic to bond the candidate ceramic to the CMC.

14 SOLAR ENERGY↗

DOE OSTI2020

Sensitivity Effects of High Temperature Overhead Conductors to Line Rating Variables

IEEE/CIGRE standards provide a base for overhead transmission line ratings Steady State Ampacity industry standard for Static Ratings using conservative environmental assumptions Measurement of many types of sensors provide a possibility to provide more capacity as a time varying capability Direct sensors of line temperature, tension, or sag provide critical, location specific information. Require complex transformation to determine line ampacity rating Are direct measurements sensors placed at key location(s)? Testing and careful calibration of sensors required Need to understand impact of uncertainties on sensors/measurements/ and forecasts

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Error field detection and correction studies towards ITER operation

In magnetic fusion devices, error field (EF) sources, spurious magnetic field perturbations, need to be identified and corrected for safe and stable (disruption-free) tokamak operation. Within Work Package Tokamak Exploitation RT04, a series of studies have been carried out to test the portability of the novel non-disruptive method, designed and tested in DIII-D (Paz-Soldan et al 2022 Nucl. Fusion62 126007), and to perform an assessment of model-based EF control strategies towards their applicability in ITER. In this paper, the lessons learned, the physical mechanism behind the magnetic island healing, which relies on enhanced viscous torque that acts against the static electro-magnetic torque, and the main control achievements are reported, together with the first design of the asynchronous EF correction current/density controller for ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Condenser Enclosure Vibration Isolation Mount Selection

A mini split cooling system will be used to maintain temperature requirements in a mobile secure transport system. While the split cooling system was designed to be used in static residential or commercial applications, it was selected for this transportation application due to a unique set of security requirements. However, the system’s ability maintain reliability and survive prolonged long-term shock and vibration is a significant concern. The mitigation strategy is to select vibration isolation mounts and perform lifetime shock and vibration testing to demonstrate survivability. The goal of this study is to generate a finite element model of the system and perform modal analysis to inform selection of vibration mounts to minimize the amount of vibrational energy transferred to the split cooling system. The scope of this report is limited to study of the condensing unit only, and geometric variation of the assembly will not be allowed.

42 ENGINEERING↗

DOE OSTI2025

Gas-Gap Calorimeter Sizing and Rating Tools for Heat Pipe Experimentation

Effective gas-gap calorimeter sizing and rating tools are required to design calorimeters that enable well-defined operating conditions, high cooling powers, and accurate calorimetry. The present report describes two tools utilizing Microsoft Excel and MathWorks MATLAB that enable the sizing and rating of gas-gap calorimeters with a He-Ar binary gas mixture in the gap. The Excel tools are two easy-to-use spreadsheets for calculating heat pipe operating temperature or He-Ar mole fractions given the required inputs. The MATLAB tool includes similar models with more robust solution algorithms along with sub-options for full-vacuum, static gas-gap, and forced circulation in the gas-gap. The accuracy of the developed tools were demonstrated by comparing with existing work in literature. The MATLAB tool was used for a parametric study to determine the gas-gap thickness, coolant gap thickness, coolant flow rate, and coolant inlet temperatures for the testing of a 3/4 in outer diameter heat pipe up to powers of 10 kW and temperatures of 1,000°C. The effects of heat pipe and calorimeter inner shell surface emissivities were investigated, considering the inability to control or accurately measure surface emissivities in most applications. It was found that controlling the He-Ar mole fractions provides a wide operating range for gas-gap thicknesses around ~ 0.042--0.090 in (~ 1.07--2.29 mm) for a surface emissivity range of 0.4--0.8, since conduction heat transfer is a significant fraction of the heat transfer across the gas-gap. In addition, it was found that turbulent flow in the coolant gap is needed at high input powers to prevent shell temperatures from approaching the boiling temperature of the water coolant. The parametric study resulted in choosing stainless steel tubes with an outer diameter and thickness of 1 x 0.065 in as the inner shell, and a 1-1/2 x 0.156 in as the outer shell of the calorimeter. Overall, this report presents the necessary information for the sizing and rating of gas-gap calorimeters with He-Ar mixtures for the testing of high-temperature heat pipes (~ 500--1,000°C).

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Reactive Extrusion of Waste Plastics with Compatibilizer and Lightly Pyrolyzed Crumb Rubber for Asphalt Modification

Modifying asphalt is a potentially high-value application for reusing waste plastics because of the high-volume usage of asphalt in highway construction. However, simply blending hot plastics and asphalt encounters difficulties related to the poor solubility of polymers, which limits the formation of a swollen network with asphalt molecules. The polymer phases also tend to coalesce and separate from asphalt during high-temperature storage in static conditions. The present study developed an innovative process to stabilize waste plastics in asphalt and improve binder storage stability by using lightly pyrolyzed crumb rubber together with a chemical compatibilizer. Both polymers were extruded to produce a thermoplastic elastomer (TPE) for asphalt modification. The mechanical performance and chemical reactions of TPEs were characterized via tension test and Fourier transform infrared spectroscopy. The storage stability and rheological properties of modified binder blends were evaluated through laboratory asphalt stability test and dynamic shear rheometer test. Polymer phases and network structures were characterized through optical microscopy. It was found that the pyrolyzed and reactive extrusion process improved the rubber solubility and polymer interaction, and therefore the storage stability of modified binder blends. The co-existence of rigid plastic and soft rubbery regimes in an entangled network provided a promising pathway to improve the mechanical performance of asphalt binders in both high- and low-temperature domains.

Ma, Yuetan↗

DOE OSTI2020

Heterogeneous Machine Learning on High Performance Computing for End to End Driving of Autonomous Vehicles

Current artificial intelligence techniques for end to end driving of autonomous vehicles typically rely on a single form of learning or training processes along with a corresponding dataset or simulation environment. Relatively speaking, success has been shown for a variety of learning modalities in which it can be shown that the machine can successfully “drive” a vehicle. However, the realm of real-world driving extends significantly beyond the realm of limited test environments for machine training. This creates an enormous gap in capability between these two realms. With their superior neural network structures and learning capabilities, humans can be easily trained within a short period of time to proceed from limited test environments to real world driving. For machines though, this gap is guarded by at least two challenges: 1) machine learning techniques remain brittle and unable to generalize to a wide range of scenarios, and 2) effective training data that enhances generalization and generates the desired driving behavior. Further, each challenge can be computationally intensive on its own thereby exasperating the gap. Moreover, is has not yet been shown that a single form of learning or training is capable of addressing a large range of scenarios. As a result, solving the first challenge does not inherently solve the second and vice versa. The work described here discusses an approach to address the first challenge that would also provide a foundation for solving the second. Our approach utilizes a combination of conditional imitation learning with a static dataset, reinforcement learning with a simulation environment, and high-performance computing to train a neural network. As a result, this reduces the “time to solution” from to the existing techniques for autonomous driving and provides an extensible framework to address the second key challenge.

autonomous vehicles↗

DOE OSTI2020

Real-time Simulation of Coordinated Sub-Transmission Volt-Var Control Tool under High Distributed PV Penetration

With the rapid penetration of intermittent solar photovoltaic (PV) and other distributed energy resources (DER) into the grid, and subsequent changes in power flow patterns in both distribution and sub-transmission, voltage regulation is becoming a major challenge. It is prudent to leverage PV and DER to provide ancillary services to the grid, such as voltage regulation. Recently, a quasi-static, coordinated real-time sub transmission volt-var control algorithm (CReST-VCT) was developed for voltage regulation under high PV penetration by dispatching the reactive power settings of the shunt devices and PV inverters. The algorithm was validated offline, on a quasistatic study. Such quasi-static dispatching algorithms cannot guarantee its performance for highly nonlinear dynamical power systems. In this paper the performance of the algorithm is validated with a real time nonlinear dynamic simulation of a modified IEEE 118 bus system in Opal-RT. The real time simulation is used to emulate the actual system operation, providing a more realistic testing environment for CReST-VCT. The dispatch and control signals are communicated between the power system (Opal solver) and the control center (GAMS solver) in real-time with a MODBUS bridge. The results demonstrate i) system is stable with the new dispatch points ii) significant improvement in system-wide voltage profiles compared to an uncontrolled scenario. Another significant contribution of the work is developing a framework for dispatchable, long duration dynamic simulations that can be leveraged for market/dispatch studies.

CReST-VCT, Opal-RT, Volt/Var Control, renewable in↗