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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A wide range experimental study and further development of a kinetic model describing propane oxidation

This work presents an experimental and kinetic modeling study of propane oxidation. Ignition delay times of propane were measured in a high-pressure shock tube and in rapid compression machines in the temperature range 689 - 1700 K at equivalence ratios of 0.5, 1.0 and 2.0 in 'air', for a wide range of pressures from 20 to 90 bar. CO and H 2 O mole fraction profiles for propane oxidation were measured in a shock tube behind reflected shock waves in the temperature range 1370-1840 K at equivalence ratios of 0.5, 1.0 and 2.0 and at a pressure of approximately 1.3 atm. Moreover, propane oxidation was studied using a jet-stirred reactor coupled to a synchrotron vacuum ultraviolet photoionization mass spectrometer at low temperatures in the range 565 - 690 K and at a pressure of 1 atm. Further, this wide range of experimental datasets for propane oxidation was used to reoptimize and update our previous kinetic mechanisms, AramcoMech3.0 and NUIGMech1.1. In the current mechanism, NUIGMech1.3, the thermo-chemical parameters of all species relevant to low-temperature propane oxidation chemistry, including propyl-peroxyl, hydroperoxyl-propyl, hydroperoxyl-propyl-peroxyl, and carbonyl-hydroperoxide radicals, are updated based on newly calculated values at the CCSD(T)-F12/TZ-F12//B2PLYPD3/TZ///B2PLYP-D3/TZ level of theory. The improvements made in the thermochemical values and in the kinetic parameters for the low-temperature propane oxidation reactions in NUIGMech1.3 result in better model agreement with the new IDTs and speciation data, including carbon monoxide, formaldehyde, propene, acetaldehyde and various minor products such as ethylene, acetic acid, acrolein as well as various hydroperoxide and cyclic ether species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A Universal Augmentation Framework for Long-Range Electrostatics in Machine Learning Interatomic Potentials

Most current machine learning interatomic potentials (MLIPs) rely on short-range approximations, without explicit treatment of long-range electrostatics. To address this, we recently developed the Latent Ewald Summation (LES) method, which infers electrostatic interactions, polarization, and Born effective charges (BECs), just by learning from energy and force training data. Here, in this study, we present LES as a standalone library, compatible with any short-range MLIP, and demonstrate its integration with methods such as MACE, NequIP, Allegro, CACE, CHGNet, and UMA. We benchmark LES-enhanced models on distinct systems, including bulk water, polar dipeptides, and gold dimer adsorption on defective substrates, and show that LES not only captures correct electrostatics but also improves accuracy. Additionally, we scale LES to large and chemically diverse data by training MACELES-OFF on the SPICE set containing molecules and clusters, making a universal MLIP with electrostatics for organic systems, including biomolecules. MACELES-OFF is more accurate than its short-range counterpart (MACE-OFF) trained on the same data set, predicts dipoles and BECs reliably, and has better descriptions of bulk liquids. By enabling efficient long-range electrostatics without directly training on electrical properties, LES paves the way for electrostatic foundation MLIPs.

Kim, Dongjin [University of California, Berkeley, ↗
DOE OSTI2026

Long-range magnetic order with disordered spin orientations in a high-entropy antiferromagnet

Disorder in magnetic systems typically suppresses long-range order, promoting short-range states such as spin glasses and magnetic clusters. This is particularly prominent in high-entropy materials, characterized by the random distributions of local magnetic entities and exchange interactions. However, in rare exceptions, long-range magnetic order can persist in high-entropy systems, while the microscopic characters and underlying mechanisms remain elusive, especially the magnetic behaviors of individual elements. Here, combining neutron diffraction and resonant soft x-ray scattering, we have conducted an element-specific investigation into the magnetic order of a high-entropy honeycomb-lattice van der Waals material (Mn 1/4 Fe 1/4 Co 1/4 Ni 1/4 )PS 3 . Despite significant atomic disorder, long-range zigzag antiferromagnetic order is observed below 72 K, with all four transition-metal elements participating in a unified phase transition. However, the spin orientations of various elements are distinct, attributed to the competition between single-ion anisotropies and exchange interactions. Our findings showcase a novel form of long-range magnetic order with disordered spin orientations, which is synergically stabilized by distinct magnetic elements in a high entropy magnet, offering a new paradigm for understanding complex magnetic systems.

Shen, Yao [Chinese Academy of Sciences (CAS), Beij↗
DOE OSTI2021

Comparison of short-range order in irradiated dysprosium titanates

Abstract The structural response of Dy 2 TiO 5 oxide under swift heavy ion irradiation (2.2 GeV Au ions) was studied over a range of structural length scales utilizing neutron total scattering experiments. Refinement of diffraction data confirms that the long-range orthorhombic structure is susceptible to ion beam-induced amorphization with limited crystalline fraction remaining after irradiation to 8 × 10 12 ions/cm 2 . In contrast, the local atomic arrangement, examined through pair distribution function analysis, shows only subtle changes after irradiation and is still described best by the original orthorhombic structural model. A comparison to Dy 2 Ti 2 O 7 pyrochlore oxide under the same irradiation conditions reveals a different behavior: while the dysprosium titanate pyrochlore is more radiation resistant over the long-range with smaller degree of amorphization as compared to Dy 2 TiO 5 , the former involves more local atomic rearrangements, best described by a pyrochlore-to-weberite-type transformation. These results highlight the importance of short-range and medium-range order analysis for a comprehensive description of radiation behavior.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Normative Ranges for Oculomotor and Reaction Time Tests in U.S. Military Service Members and Veterans

AbstractBackground Oculomotor and reaction time tests are frequently used assessments of vestibular symptoms, traumatic brain injury (TBI), or other neurological disorders in both clinical and research contexts. When interpreting these tests it is important to have a reference interval (RI) as a comparison for what constitutes a typical/expected response; however, the current body of research has only limited information regarding normative ranges calculated according to established standards or for a military-specific sample.Purpose The purpose of the present study was to describe RIs for oculomotor and reaction time tests in a cohort of service members and veterans (SMVs) for use as comparators by clinicians and scientists.Research Design Descriptive.Study Sample Participants were prospectively enrolled in the Defense and Veterans Brain Injury Center-Traumatic Brain Injury Center of Excellence 15-year Longitudinal Traumatic Brain Injury Study. Only SMVs without a history of TBI or blast exposure were included in the RI calculations.Data Collection and Analysis The test paradigms included in this analysis were: smooth pursuit, prosaccades, antisaccades, saccades and reaction time, predictive saccades, optokinetic nystagmus, auditory reaction time, and visual reaction time. Nonparametric methods, based on the U.S. Food and Drug Administration's recognized consensus standards, were used to calculate 95% RIs. A comparison between the calculated RIs and those available from previously published research is provided.Results Summary statistics and RIs were calculated for 47 outcome parameters from 13 oculomotor and reaction time tests. Sample sizes and age ranges varied across outcome parameters depending on the availability of reference values for RI calculations. The sample sizes used to calculate RIs ranged from 51 to 69. The age of SMVs included in each RI ranged from 19 to 61 years with mean ages ranging from 37 to 39 years. Similarities/differences between the RIs in the present study and those in previously published research are highly dependent on the outcome parameter; however, in general, the RIs in the present study tended to be somewhat wider.Conclusion The RIs provided in this paper can serve as comparisons for clinicians and scientists who are utilizing these oculomotor and reaction time testing paradigms in similar cohorts of patients or research participants.

Audiology & Speech-Language Pathology↗
DOE OSTI2022

A deep potential model with long-range electrostatic interactions

Machine learning models for the potential energy of multi-atomic systems, such as the deep potential (DP) model, make molecular simulations with the accuracy of quantum mechanical density functional theory possible at a cost only moderately higher than that of empirical force fields. However, the majority of these models lack explicit long-range interactions and fail to describe properties that derive from the Coulombic tail of the forces. To overcome this limitation, we extend the DP model by approximating the long-range electrostatic interaction between ions (nuclei + core electrons) and valence electrons with that of distributions of spherical Gaussian charges located at ionic and electronic sites. The latter are rigorously defined in terms of the centers of the maximally localized Wannier distributions, whose dependence on the local atomic environment is modeled accurately by a deep neural network. In the DP long-range (DPLR) model, the electrostatic energy of the Gaussian charge system is added to short-range interactions that are represented as in the standard DP model. The resulting potential energy surface is smooth and possesses analytical forces and virial. Missing effects in the standard DP scheme are recovered, improving on accuracy and predictive power. By including long-range electrostatics, DPLR correctly extrapolates to large systems the potential energy surface learned from quantum mechanical calculations on smaller systems. We illustrate the approach with three examples: the potential energy profile of the water dimer, the free energy of interaction of a water molecule with a liquid water slab, and the phonon dispersion curves of the NaCl crystal.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Singularities in the gravitational capture of dark matter through long-range interactions

Here, we re-examine the gravitational capture of dark matter (DM) through long-range interactions. We demonstrate that neglecting the thermal motion of target particles, which is often a good approximation for short-range capture, results in parametrically inaccurate results for long-range capture. When the particle mediating the scattering process has a mass that is small in comparison to the momentum transfer in scattering events, correctly incorporating the thermal motion of target particles results in a quadratic, rather than logarithmic, sensitivity to the mediator mass, which substantially enhances the capture rate. We quantitatively assess the impact of this finite temperature effect on the captured DM population in the Sun as a function of mediator mass. We find that capture of DM through light dark photons, as in e.g. mirror DM, can be powerfully enhanced, with self-capture attaining a geometric limit over much of parameter space. For visibly-decaying dark photons, thermal corrections are not large in the Sun, but may be important in understanding long-range DM capture in more massive bodies such as Population III stars. We additionally provide the first calculation of the long-range DM self-evaporation rate.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Needle bacterial community structure across the species range of limber pine

Abstract Bacteria on and inside leaves can influence forest tree health and resilience. The distribution and limits of a tree species’ range can be influenced by various factors, with biological interactions among the most significant. We investigated the processes shaping the bacterial needle community across the species distribution of limber pine, a widespread Western conifer inhabiting a range of extreme habitats. We tested four hypotheses: (i) Needle community structure varies across sites, with site-specific factors more important to microbial assembly than host species selection; (ii) dispersal limitation structures foliar communities across the range of limber pine; (iii) the relative significance of dispersal and selection differs across sites in the tree species range; and (iv) needle age structures bacterial communities. We characterized needle communities from the needle surface and tissue of limber pine and co-occurring conifers across 16 sites in the limber pine distribution. Our findings confirmed that site characteristics shape the assembly of bacterial communities across the host species range and showed that these patterns are not driven by dispersal limitation. Furthermore, the strength of selection by the host varied by site, possibly due to differences in available microbes. Our study, by focusing on trees in their natural setting, reveals real needle bacterial dynamics in forests, which is key to understanding the balance between stochastic and deterministic processes in shaping forest tree-microbe interactions. Such understanding will be necessary to predict or manipulate these interactions to support forest ecosystem productivity or assist plant migration and adaptation in the face of global change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Short-range magnetic order and planar anisotropy in the topological ferrimagnet Mn 3 ⁢Si 2 ⁢Te 6

Mn 3 ⁢Si 2 ⁢Te 6 is a ferrimagnetic topological nodal-line semiconductor that exhibits unconventional colossal magnetoresistance behavior, with short-range spin fluctuations being potentially intimately linked to the emergent properties. Here we determine the short-range magnetic order and anisotropy through total neutron scattering and polarized neutron powder diffraction measurements on polycrystalline Mn 3 ⁢Si 2⁢ Te 6 . Strong in-plane anisotropy is quantified on the Mn ions through extraction of the local site susceptibility tensor. Here, the real-space local spin structure is determined through the application of magnetic pair distribution function analysis covering a wide temperature range. Short-range order over a locally frustrated trimer of three nearest neighbors is found to exist well above the long-range ferrimagnetic transition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Signaling and scrambling with strongly long-range interactions

Strongly long-range interacting quantum systems—those with interactions decaying as a power law 1/$r^α$ in the distance $\textit{r}$ on a $\textit{D}$-dimensional lattice for $\textit{α ≤ D}$—have received significant interest in recent years. They are present in leading experimental platforms for quantum computation and simulation, as well as in theoretical models of quantum-information scrambling and fast entanglement creation. Since no notion of locality is expected in such systems, a general understanding of their dynamics is lacking. In a step towards rectifying this problem, we prove two Lieb-Robinson-type bounds that constrain the time for signaling and scrambling in strongly long-range interacting systems, for which no tight bounds were previously known. In this work, our first bound applies to systems mappable to free-particle Hamiltonians with long-range hopping, and is saturable for $\textit{α ≤ D/2}$. Our second bound pertains to generic long-range interacting spin Hamiltonians and gives a tight lower bound for the signaling time to extensive subsets of the system for all $\textit{α < D}$. This many-site signaling time lower bounds the scrambling time in strongly long-range interacting systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Voltage-controlled long-range propagation of indirect excitons in a van der Waals heterostructure

Indirect excitons (IXs), also known as interlayer excitons, can form the medium for excitonic devices whose operation is based on controlled propagation of excitons. Here, a proof of principle for excitonic devices was demonstrated in GaAs heterostructures where the operation of excitonic devices is limited to low temperatures. IXs in van der Waals transition-metal dichalcogenide (TMD) heterostructures are characterized by high binding energies making IXs robust at room temperature and offering an opportunity to create excitonic devices operating at high temperatures suitable for applications. However, a characteristic feature of TMD heterostructures is the presence of moiré superlattice potentials, which are predicted to cause modulations of IX energy reaching tens of meV. These in-plane energy landscapes can lead to IX localization, making IX propagation fundamentally different in TMD and GaAs heterostructures and making uncertain whether long-range IX propagation, sufficiently long to allow for creating elaborate excitonic devices and circuits, can be realized in TMD heterostructures. In this work, we realize long-range IX propagation with the 1/e IX luminescence decay distances reaching 13 microns in a MoSe 2 /WSe 2 heterostructure. We trace the IX luminescence along the IX propagation path. In the presented TMD materials, the long-range IX propagation occurs up to ~50 K. This is a step toward the room temperature operation, which can be realized in TMD heterostructures due to the high IX binding energy. We also realize control of the long-range IX propagation by voltage. The IX luminescence signal in the drain of an excitonic transistor is controlled within 40 times by gate voltage. The control of the IX propagation in the MoSe 2 /WSe 2 heterostructure is governed by new mechanisms, beyond the mechanism for controlling IX transport by an energy barrier to IX propagation (or a trap for IXs) created by the gate electrode, known since the studies of GaAs heterostructures. We discuss the origin of the voltage-controlled long-range IX propagation in the MoSe 2 /WSe 2 heterostructure, in particular, the electric-field control of the moiré potential.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Nucleation and growth of polar clusters with in-phase tilts into a long-range ferroelectric matrix in a sodium niobate based complex relaxor

In this study, we have investigated the temperature dependence of atomic ordering at multiple length scales in a lead-free sodium niobate-based relaxor, i.e., 0.75 NaNbO 3 -0.25 Ba 0.9⁢ Ca 0.1⁢ TiO 3 (NN-25BCT) via synchrotron x-ray diffraction, Raman spectroscopy, and pair distribution function analysis. High-resolution synchrotron x-ray powder diffraction (SXRD) measurements reveal a ferroelectric phase transition in the relaxor ferroelectric NN-25BCT below the Vogel-Fulcher freezing temperature (𝑇 VF ≈ 270 K). In addition, SXRD analysis demonstrates the competition between in-phase octahedral tilting and ferroelectric order at the long-range scale using mode crystallography. On the other hand, Raman spectroscopic analysis provides evidence of polar ordering for 𝑇 > 𝑇 VF (with tetragonal symmetry) persisting up to the Burns temperature (𝑇 B ). Furthermore, pair distribution function (PDF) analysis reveals the presence of a polar antiferrodistortive tetragonal phase with 𝑃⁢4⁢𝑏𝑚 space group at short ranges throughout the studied temperatures (i.e., 110 K ≤ 𝑇 ≤500 K), irrespective of nonpolar long-range ordering above 𝑇 VF . Therefore, our measurements provide direct evidence for the presence of polar ordering at short ranges and their gradual transformation into long-range polar ordering using an integrated multiscale structural analysis. In conclusion, as a result of a transition from relaxor to a ferroelectric phase in the vicinity of room temperature, NN-25BCT can be exploited for applications in pyroelectric detectors, electrocaloric devices, and multilayered ceramic capacitors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Offset lock with a 440-GHz range using electro-optic modulation

Offset locking is crucial to many physics experiments. Wide range offset locks are desirable, as they increase the span of usable frequencies in an experiment. Here, we experimentally realize a wide-range offset lock using a beat-note setup combined with electro-optic phase modulation. By using frequency down-conversion of the beat note and locking to sidebands generated by electro-optic modulation, we achieve an offset range of ± 220.1 GHz with offset frequency fluctuations under 0.1 Hz and a phase error variance of 0.017 rad 2 over a 100 kHz bandwidth, greatly widening the range compared to past setups using this method. The relative simplicity of our setup provides a compelling method for locking at offsets in the hundreds of GHz range.

Zhou, Ocean (ORCID:0000000279192636)↗
DOE OSTI2020

Cummins Electric Truck with Range-Extending Engine (ETREE) Project (Final Technical Report)

The Cummins Electric Truck with Range Extending Engine (ETREE) program designed, developed, and demonstrated a range extending electric vehicle that employs an electrified propulsion system installed in a class 6 commercial vehicle (Peterbilt 220). This project was relevant to industry and the greater public because at the time of the project there were two keys to widespread electrified commercial vehicle adoption yet to be realize: 1) For pure electrified vehicle adoption, battery improvements are needed: Cost must decrease, and energy density must increase. 2) Electric vehicles must overcome fleet operator risks such as: operations in cold climates, hilly terrain, or where majority of conventional trucks are replaced with electrified vehicles. In the near to medium term these adoption hurdles were address by the objectives of this project. A plug-in hybrid vehicle that could be operated in all electric mode for most of its workday optimizing the use of grid energy with the ability to supplement energy demand with the onboard range extending engine. This project’s architecture provided ability to match a conventional class 6 commercial vehicle range and performance characteristics prior to the ubiquitous adoption of battery electric vehicle charging infrastructure as well. Additionally, the vehicles produced as part of this project can be considered a prototype for a commercially viable heavily electrified commercial vehicle because most of the physical hardware used for the project is commercially available in the market today. The ETREE program met its main objectives and demonstrated 65% fuel consumption reduction as compared to a conventional class 6 vehicle while meeting performance and range expectations. This was achieved by drawing upon the strengths of the assembled team: Cummins, PACCAR, the Ohio State University, Argonne National Laboratory and the National Renewable Energy Laboratory.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

An extrapolation method for strain ranges and hold times in developing the EPP+SMT creep-fatigue design curves for Alloy 617

Experimental and numerical studies in developing the integrated Elastic–Perfectly Plastic (EPP) plus Simplified Model Test (SMT) design methodology, referred to as the EPP+SMT method, continued in FY2022. This report focuses on the methods for extrapolating the EPP+SMT creep-fatigue (CF) design curves at long hold times and low strain ranges. In this study, the available CF failure data on Alloy 617 at 950°C were analyzed to determine a set of CF failure criteria. At very low strain ranges and long hold times, CF failure data are not accessible by experiments because of the extraordinarily long test durations and the inability of the test machines to accurately control these small strain ranges. A CF experimental approach with the concept of block-strain range CF testing protocol was developed. Tests using this protocol were conducted to generate the needed information for calibrating material parameters of the numerical material models. The Time Fraction based method and Dissipated Energy method were used to extrapolate the CF life curves to low strain ranges and long hold times. Based on the new experimental approach and CF life prediction methods, the CF life curves with various hold times were developed for Alloy 617 at 950°C. In addition, an experiment was designed and is being performed to verify the predicted CF curves at 950°C. The extrapolation procedure will be applied at lower temperatures to complete the development of the EPP+SMT CF design curves for Alloy 617 in F2023.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Extrapolation of the Rainflow-Counted Load Ranges for Fatigue Assessment of the Wind Turbine's Blades

Wind turbine design standards recommend the use of statistical modeling coupled with extrapolation of the short-term load data to long-term periods for fatigue reliability assessment. However, statistical error and computational expense can limit the accuracy of such approaches. In the case of wind turbine blades, the errors are more significant because of the high material fatigue exponent that makes the damage estimations more sensitive to variations. In addition, due to different excitation sources, the flapwise load range histogram is not unimodal, and thus its statistical modeling is complex. In the present work, we provide three methods for statistical modeling of the flapwise bending moment ranges including a novel approach based on frequency-based separation of the modes. The first two methods are simplified approaches for modeling the most crucial load ranges using unimodal distributions and the third method involves multimodal distribution fitting. The research is based on 3600 10-minute aeroelastic simulations of DTU 10MW case study wind turbine from which a benchmark damage equivalent load (DEL) is calculated. The DEL calculated by each of the three proposed methods is compared to this reference. The results show that the conventional approach based on using 6 seeds as well as using mixture models fitted on the limited data lead to under-conservative results with errors up to 23%. On the other hand, the simplified unimodal approaches provided in this work can provide conservative estimations of the fatigue damage with mean values 5% and 12% higher than the benchmark. However, the variability of the DEL estimates is higher when using unimodal extrapolation of the load ranges, and the data can be conservative by 17.5%. The proposed unimodal fits suggested for modeling and extrapolation of the blade's load ranges provide less errors relatively and most importantly conservative DEL estimations while maintaining computational efficiency.

blade fatigue↗
DOE OSTI2023

Certifiably Correct Range-Aided SLAM

We present the first algorithm capable of efficiently computing certifiably optimal solutions to range-aided simultaneous localization and mapping (RA-SLAM) problems. Robotic navigation systems are increasingly incorporating point-to-point ranging sensors, leading state estimation which takes the form of RA-SLAM. However, the RA-SLAM problem is more difficult to solve than traditional pose-graph SLAM; ranging sensor models introduce additional non-convexity, unlike pose-pose or pose-landmark measurements, a single range measurement does not uniquely determine the relative transform between the involved sensors, and RA-SLAM inference is highly sensitive to initial estimates. Our approach relaxes the RA-SLAM problem to a semidefinite program (SDP), which we show how to solve efficiently using the Riemannian staircase methodology. The solution of this SDP provides a high-quality initialization for our original RA-SLAM problem, which is subsequently refined via local optimization, as well as a lower-bound on the RA-SLAM problem's optimal value. Our algorithm, named certifiably correct RA-SLAM (CORA), applies to problems comprised of arbitrary pose-pose, pose-landmark, and ranging measurements. Evaluation on simulated and real-world marine examples shows that our algorithm frequently produces certifiably optimal RA-SLAM solutions; moreover, even suboptimal estimates are typically within 1-2\% of the optimal value.

Papalia, Alan↗
DOE OSTI2021

Assembling a Cyber Range to Evaluate Artificial Intelligence / Machine Learning (AI/ML) Security Tools

In this case study, we will describe the design and assembly of a cyber security test range we have built at Oak Ridge National Laboratory in Oak Ridge, TN, USA. The range is designed to provide a flexible environment to evaluate cyber security tools—particularly those involving AI/ML—in a way that provides realistic environments and where we can control the experiments to determine the strengths and weaknesses of the tools. We have designed in the ability to repeat the evaluations, so additional tools can be evaluated and compared at a later time. The system is one that can be scaled up or down for experiment sizes. At the time of the conference we will have completed two full-scale, national, government challenges on this range. These challenges are evaluating the performance and operating costs for AI/ML-based cyber security tools for application into large, government-sized environments. These evaluations will be described, in order to provide motivation and context for various design decisions and adaptations we have made. The first challenge measured end-point security tools against 100K malware samples chosen across a range of types. The second is network detection of attempted penetration and exploitations with varying levels of covertness in a high-volume, business network. The scale of each of these challenges is requiring us to create automation systems to repeat the experiments identically for each tool. Preventing there being easy signs of malicious activity for the AI/ML tools to focus on has been a particularly interesting and challenging aspect of designing and executing these challenge events. After the events, the range continues to be used for other research such as adversarial machine learning where the repeatability, scale, and automation required for the national challenge events become essential elements for research.

Nichols, Jeff↗