SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
This chapter discusses risks from unintentional or illicit movement of nuclear and radioactive material out of regulatory control through international border crossing points, summarizes international efforts to build capacity and support border security, and discusses how detection equipment can be used to screen for penetrating radiation at traditional border crossing points.
Effective border security is essential for maintaining national safety and managing immigration. This helps prevent illegal activities such as smuggling, trafficking, and unauthorized entry. Traditional methods of border monitoring are heavily reliant on human patrols which can be inadequate given the cost and labor-intensity given the challenging terrain involved. This report presents an advanced unmanned solution designed to significantly enhance border security through currently used drone technology using integrated autonomy by the adoption of ORNL’s sophisticated software platform known as Mapster-Nomad.
There are several U.S. government-sponsored programs with significant experience engaging with foreign government and industry partners to support capacity-building in export controls. This work seeks to answer the question: How can the outreach experience of the U.S. government-sponsored export control capacity-building programs (ECCBP) inform best practices for engaging with advanced reactor vendors in the domain of international nuclear safeguards? To answer this question, we interviewed export control subject matter experts with experience working for the U.S. ECCBPs – the Bureau of Industry and Security (BIS), the Export Control and Related Border Security (EXBS) program, and the International Nonproliferation Export Control Program (INECP) – and developed a set of recommendations for industry engagement based on the collective experience of interviewees.
The continued operation of Land Ports of Entry (LPOE), managed by the Customs and Border Protection (CBP) and General Services Administration% is vital to the U.S. economy and security. Border faculties are included in the Department of Homeland Security (DHS) Government Facilities Sector2, one of the 16 critical infrastructures "whose assets, systems, and networks, whether physical or virtual, are considered so vital to the United States that their incapacitation or destruction would have a debilitating effect on security, national economic security, national public health or safety, or any combination thereof.'" Specifically, disruptions to the flow of border crossing traffic, in the form of closures or increased border crossing wait times, impact the economy and security of all countries involved. This paper describes a process for analyzing and improving the resilience of U.S. Land Ports of Entry. For LPOE, the team believes that energy resilience is the primary objective due to the complete reliance on the e-manifest system and the increasing use of Multi-Energy Portals (MEPs). Emanifests are part of CPB's Automated Commercial Environment (ACE). They document several key pieces of information about cargo vehicles wishing to cross the border into the United States and are submitted before arriving at the port. Vehicles can be flagged for more invasive inspection based on the content of the e-manifest. MEPs are a non-intrusive inspection (NII) technology used to scan the contents of the cargo. Together MEPs and ACE serve an important role in aiding CBP with their mission to protect "the public from dangerous people and materials", and "enabling legitimate trade and travel.'" To analyze resilience of a port, the team would need to understand the port's current energy usage, which systems depend on energy and what backup systems exist, and any emergency operation plans that dictate how systems are operated in the event of a power outage. The team would also need to determine the design basis threats (DBTs) for the LPOE which could include natural disasters, manmade events, and accidents. The magnitudes of the DBTs are calculated and are then translated to expected impacts on the infrastructure and systems at the port. With this information gathered, existing LPOE models developed here at Sandia National Laboratories could be extended to support decisions about resilience. Current models are implemented in FlexSim, a 3rd party discrete event simulator. FlexSim provides 3-D visuals of physical layout that can reveal valuable insights, allows input to be variable (e.g. time it takes to interact with the CBP officer at primary inspection can vary) so that a whole range of possibilities can be captured in the results, and can be used to collect user-defined output metrics. Current LPOE models focus on cargo vehicle traffic, and process changes caused by the installation of new drive-through MEPs. Extending them to address resilience questions would require the addition of key pieces of information learned during the resilience analysis including critical systems, failure rates, and process changes for when failures occur. The primary output metric for current models is border crossing wait time. Additional metrics would also be added to the model to gain a more complete understanding of impacts related to resilience, for example, MEP scan rate. Once complete, the model could be used to analyze the effectiveness of mitigation strategies representing some future state.
Radiation portal monitors (RPMs) are widely used at border security checkpoints to detect the presence of radioactive materials in people, vehicles, and cargo. Typically, RPM detection systems consist of two pillars equipped with gamma and neutron detectors. To improve detection efficiency, RPMs employ techniques such as a limited energy window, dynamic alarm thresholds, and lead shielding. However, without continuous monitoring of background radiation, signal interpretation can be compromised, because environmental factors and mechanical failures can cause fluctuations. Here, we introduce a daily file format that logs gamma background and neutron background radiation levels continuously over a 24 h period; this format is different from traditional formats that record data only when the RPM is active or occupied. The approach enables RPM operators and analysts to (1) identify and diagnose malfunctioning components, (2) adjust system settings to account for dynamic environmental factors, and (3) use the recorded data to characterize outer space phenomena. Continuous background reporting is essential for identifying issues such as faulty connections, voltage divider failures, and errors in background updates. Continuous background reporting also enables the detection of external influences, including nearby X-ray scanners, temperature fluctuations, rainfall, cosmic radiation, and lunar phase changes. These data files are designed to be easily evaluated and parsed using common tools, and a quick review by an expert is often sufficient for problem diagnosis. We anticipate that continuous background radiation monitoring and these new strategies will significantly improve the accuracy and reliability of RPM systems, reducing the rate of false alarms and enhancing overall system performance.
The considerable body of data available for evaluating biometric recognition systems in Research and Development (R&D) environments has contributed to the increasingly common problem of target performance mismatch. Biometric algorithms are frequently tested against data that may not reflect the real world applications they target. From a Testing and Evaluation (T&E) standpoint, this domain mismatch causes difficulty assessing when improvements in State-of-the-Art (SOTA) research actually translate to improved applied outcomes. This problem can be addressed with thoughtful preparation of data and experimental methods to reflect specific use-cases and scenarios.To that end, this paper evaluates research solutions for identifying individuals at ranges and altitudes, which could support various application areas such as counterterrorism, protection of critical infrastructure facilities, military force protection, and border security. We address challenges including image quality issues and reliance on face recognition as the sole biometric modality. By fusing face and body features, we propose developing robust biometric systems for effective long-range identification from both the ground and steep pitch angles. Preliminary results show promising progress in whole-body recognition. This paper presents these early findings and discusses potential future directions for advancing long-range biometric identification systems based on mission-driven metrics.
As concerns about the illicit movement of radioactive materials across international borders increase, so too has the need for increased protection of those borders both foreign and domestic. The challenge is not only to detect hidden radioactive materials, but also to distinguish them from legitimate radionuclides such as radio-pharmaceuticals that are often transported across borders and shipped throughout a country. With more than 600 U.S. border sites to protect, screening imported radioactive material requires a careful balance of high throughput and high search efficiency. However, these requirements are difficult to meet as rapid screening operations leave less time for radiation detectors to efficiently evaluate materials. In support of border security, Sandia developed organic glass scintillators.
Screening and inspection of cargo containers are two essential methods to nondestructively examine the contents of shipment. These methods enable the detection of illicit transportation of unauthorized materials such as nuclear and radioactive materials, explosives, drugs, and so on, typically at borders or secure facilities. Although high-energy X-ray transmission is a standard system and is widely used for cargo inspection, the inherent challenges of high false-positive rates and high attenuation factors necessitate the development of complementary techniques that can increase the detection efficiency and accuracy in large and dense materials. Gamma-rays, which possess higher penetration characteristics because of their high energy, offer an alternative nonintrusive modality for cargo scanning. They represent a promising inspection method when compared to X-rays for three reasons: (1) improved ability to detect nuclear and radioactive materials, (2) higher inspection throughput rates, and (3) lower false-positive rates. Currently, there are two main gamma-ray inspection techniques, active and passive interrogation. Active interrogation can be further grouped into (1) gamma-ray transmission imaging and (2) neutron-induced gamma-ray emission detection. Gamma-ray transmission imaging utilizes differences in material densities for mapping the shipment contents and detecting anomalies. It is analogous to the X-ray transmission method; however, the high-energy photons make it more difficult to shield against, which enables more efficient performance in large and dense material inspection. Neutron-induced gamma-ray emission inspection is designed for the detection of nuclear and radioactive material because those materials emit characteristic gamma-rays when they are activated by neutron absorption. On the other hand, passive interrogation techniques rely on high-efficiency detectors to detect radiation emitted from hidden special nuclear or other radioactive materials. Similar to passive interrogation, cosmic ray muon monitoring and imaging are relatively new techniques that do not require external radioactive sources. These techniques have received attention as a potential next-generation radiographic probe to identify illicit transportation of nuclear and radioactive materials in cargo containers. Cosmic ray muons have unique features, (1) much higher energies than X-rays or gamma-rays (on the order of 10−1—104 GeV), (2) enhanced penetration capability, and (3) natural occurrence, thereby eliminating the need for induced radiation sources. These features enable cosmic ray muons to be utilized for detection of special nuclear materials in high-background-noise environments. By analyzing incoming and outgoing muon trajectories, scattering angles, and energies, it has been shown that it would be possible to locate hidden and well-shielded materials in cargo containers via three-dimensional muon tomography images or signal analysis. Gamma-rays, cosmic ray muons, and other nonintrusive cargo inspection modalities are complementary to each other, allowing them to address various cargo inspection conditions (i.e., scanning time, cost, radiation exposure level, and types of target materials). This chapter presents a detailed review of the theoretical fundamentals and technical principles behind the current gamma-ray and cosmic ray muon modalities for cargo inspection. Additionally, critical assessments and suggestions for the future directions to advance the use of gamma and muon modalities are discussed.
Vapor detection is a noncontact sampling method, which is a less invasive means of explosives screening than physical swiping. Explosive vapor detection is a challenge due to the low levels of vapors available for detection. This study demonstrates that the parts-per-quadrillion sensitivity of atmospheric flow tube-mass spectrometry (AFT-MS) combined with a high-volume air sampler enables standoff detection of trace explosives vapor at distances of centimeters to meters. Standoff detection of explosives vapor was possible both upstream and downstream of the vapor source relative to room air currents. RDX vapor from a saturated source was detected at up to 2.5 m. Vapors from RDX residue and nitroglycerin residue were detected at distances up to 0.5 m. The sampling can be optimized by accounting for air movement in the room or environment, which could further extend standoff detection distances. In conclusion, using AFT-MS with a high-volume sampler could also be effective for standoff vapor detection of drugs and additional chemical threats and could be useful for security screening applications such as at mail facilities, border crossings, and security checkpoints.
Inspecting vehicles and containers for the presence of nuclear material is a challenging task for border control and security. When performed manually by inspectors, this task also has an associated risk of exposing the inspectors to unknown radiation. With the advent of agile, easy-to-program, quadruped robots like the Boston Dynamics Spot, automation of secondary inspection can improve the efficiency of the inspection process and alleviates the radiation risks to inspectors. In this project, Brookhaven National Laboratory and the University of Massachussetts at Lowell explored how to automate a simple secondary inspection mission. The Spot robot comes with its own software development kit (SDK) that allows clients/users to write custom code in the Python programming language to control the robot. Spot also has a payload computer called Spot-CORE, which runs the Ubuntu Linux operating system and allows users to integrate external sensors, such as a radiation detector, with Spot. In this study, the Kromek D3S detector has been integrated with Spot via the Spot-CORE, allowing Spot to capture gamma spectra and neutron counts for a specified acquisition period. Two custom routines, search and confirmation, have been developed and executed in this specified order. The search routine directs Spot to go around the nearest obstacle, e.g., vehicle and container, in a preset distance and step to collect gamma and neutron gross counts with the D3S detector. The radiation data and the robot location corresponding to each step are stored and fed to the confirmation routine at the end of the search. The confirmation routine then navigates Spot to the locations of the highest gamma or neutron counts to perform a long, e.g., one minute, measurement, and gives the operators the signature gamma spectra and neutron counts at the hotspots. This paper presents a detailed description of this automated system along with results of the preliminary tests in identifying the location and signature of a 137Cs radiation source in a vehicle.
Radiation detectors are crucial in a wide variety of research and commercial applications, such as oil and gas exploration, medical imaging, nuclear nonproliferation, and homeland security. Neutron and gamma-ray detectors are fundamental components in portal monitors at ports and border crossings, bolstering national security against radiological threats. This study presents a dual-mode scintillator, undoped and Tl-doped 6 Li-Cs 3 Cu 2 I 5 , and demonstrates its potential as a promising material for simultaneous thermal neutron and gamma-ray detection. We explore the Bridgman growth of both undoped and thallium doped Li → Cu and Li → Cs substitutional systems with various Li doping levels and assess their impact on scintillation properties. Under 662 keV gamma-ray excitation, the undoped crystals had light yields up to 35,900 ph/MeV, with energy resolutions down to 4.5%. The Tl-doped crystals performed better than the undoped crystals with light yields peaking at 65,900 ph/MeV and energy resolutions as low as 3.5%. When exposed to a moderated 252 Cf excitation source, our crystals had light yields between 102,900 and 167,200 photons per thermal neutron capture, with a full energy thermal neutron peak reaching 3 MeV in gamma equivalent energy. Pulse shape discrimination studies reveal well-separated gamma and neutron events, resulting in Figure-Of-Merit (FOM) as high as 3.7. Furthermore, these findings highlight the potential of Li-doped Cs 3 Cu 2 I 5 as a viable candidate for next-generation dual-mode scintillators.
Illicit tunneling along the U.S. Mexican border is a persistent national security problem. Several types of sensors could be to used to detect tunnels, but the hydrogeology of the subsurface makes some technologies ineffective. This effort used available borehole and surface geology data to develop 3D hydrogeologic models, which could then provide the input for optimizing subsurface sensor technologies to detect tunnels. Depending on the specific type of sensor, the following physical properties of the subsurface are important: longitudinal speed (velocity-p), shear speed (velocity-s), acoustic attenuation, electrical permittivity, electrical conductivity, density and elastic properties. LLNL developed a procedure which uses hydrogeological datasets to determine 3D hydrogeology cross sections. The physical properties of the rocks are generally not known precisely, thus ranges of properties would need to be considered. This cross-section data can then be utilized to enhance modeling studies to optimize sensor types/systems.
Cesium Hafnium Chloride (Cs2Hfl6) is a promising metal halide scintillating detector due to its excellent characteristics such as non-hygroscopicity, high light yield without doping. Scintillators plays an important role in nuclear security applications as detectors at border monitoring stations. We grew and characterized CHC crystals to be fabricated for gamma detection. Photoluminescence was performed using the Duetta Fluorescence and Absorbance Spectrometer. The energy response to Cs-137 and Co-60 reference sources was recorded for a representative sodium iodide (NaI) scintillating detector.
Power engineers rely on computer-based simulation tools to assess grid performance and ensure security. At the core of these tools are solvers for sparse linear equations. When transformed into a bordered block-diagonal (BBD) structure, part of the sparse linear equation solving can be parallelized. This work focuses on using the Schur-complement-based method for LU factorization on BBD matrices, specifically, Jacobian matrices from large-scale systems. Our findings show that the natural ordering method outperforms the default ordering method in computational performance for each block of the BBD matrix. This observation is validated using synthetic 25k-bus and 70k-bus cases, showing a speedup of up to 38% when using natural ordering without permutation. Additionally, the impact of the number of partitions is studied, and the result shows that computational performance improves with more, smaller partitions in the BBD matrices.
The electricity sector is a substantial source of air pollution and associated health problems in South Asia and elsewhere. Fossil-fueled power plants emit a wide variety of harmful pollutants. Those with the greatest health impacts are particulate matter and ozone. Once released into the atmosphere, there is no practical way to remove air pollutants, which means that policies designed to improve air quality have to limit the pollutants before release. However, tackling such pollution is challenging because developing economies also need to provide electricity as a basic necessity for their citizens and as an engine of economic growth. This report provides examples of policies impacting air pollution from the fossil-fuel electricity sector in the South Asian countries of Afghanistan, Bangladesh, Bhutan, India, the Maldives, Nepal, Pakistan, and Sri Lanka. Some of this information was difficult to locate, so this is not a comprehensive study, but rather an overview or "scan" of the sector that includes examples of (1) policies that directly regulate air quality by limiting emissions from specific point sources (by restricting operating hours, for instance), and (2) indirect policies that incentivize or disincentivize polluting activities, such as policies to encourage fuel switching, for example. The report shows (1) the great variation among the policy instruments used in each country, (2) that many countries, especially those that have a mismatch between seasonal demand and resource availability, could improve energy security and reduce air pollution through increased cross-border electricity trade, and (3) some countries have contradictory policies (promoting both coal and renewables, for instance).
The electricity sector is a substantial source of air pollution and associated health problems in Central Asia and elsewhere. Fossil-fueled power plants emit a wide variety of harmful pollutants and their chemical precursors. The pollutants with the greatest health impacts are particulate matter and ozone. Once released into the atmosphere, there is no practical way to remove air pollutants, which means that policies designed to improve air quality have to limit the pollutants before release. However, tackling such pollution is challenging, particularly in developing economies, due to the need to provide electricity as a basic necessity for citizens and as an engine of economic growth. This report provides examples of policies impacting air pollution from the electricity sector in the Central Asian countries of Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan. It is a partner publication to an earlier report that addressed policies in South Asia. As with the South Asia report, information on policies in some countries was difficult to locate; therefore, this is not a comprehensive study, but rather an overview or "scan" of the sector that includes examples of: (1) policies that directly regulate air quality by limiting emissions from specific point sources (by restricting operating hours, for instance); and (2) indirect policies that incentivize or disincentivize polluting activities, such as policies to encourage fuel switching to or from cleaner renewable resources. Note that this report was prepared before the Russia-Ukraine conflict and therefore doesn't address consequences of that war for Central Asia. The report finds: (1) That Central Asian countries typically have relatively few policy instruments available for regulating national air emissions; (2) That many countries, especially those that have a mismatch between seasonal demand and resource availability, could improve energy security and reduce air pollution through increased cross-border electricity trade; (3) That some countries have seemingly contradictory policies (promoting both coal and renewables, for instance). This report is also available in Russian: https://www.nrel.gov/docs/fy23osti/85192.pdf.
Smuggling of special nuclear materials and nuclear devices through borders and ports of entry constitutes a major risk to global security. Technologies are needed to reliably screen the flow of commerce for the presence of high-Z materials such as uranium and plutonium. Here, we present an experimental proof-of-concept of a technique that uses inelastic (p,p') nuclear reactions to generate monoenergetic photons, which provide means to measure the areal density and the effective-Z (Z eff ) of an object with an accuracy surpassing that achieved by current methods. We use an ION-12 SC superconducting 12 MeV proton cyclotron to produce 4.4, 6.1, 6.9, and 7.1 MeV photons from a variety of nuclear reactions. Using these photons in a transmission mode, we show that we are able to accurately reconstruct the areal densities and Zeff of a test object. This methodology could enable mobile applications to screen commercial cargoes with high material specificity, providing a means of distinguishing common cargo materials from high-Z materials that include uranium and plutonium.
The deployment of zero carbon renewable energy sources needs to increase significantly to support the goal of net zero greenhouse gas emissions by 2050. At the same time energy end use needs to decarbonize. This will change both energy supply and energy demand patterns, requiring the energy delivery infrastructure (grid-based transmission circuits) to become increasingly flexible to maintain security of supply everywhere and always. The integration of zero carbon renewable energy requires cross-border and cross energy system coupling and a fit-for-purpose design. Nowadays, energy systems are planned, designed and operated in silos with a strong national focus. However, large-scale offshore wind production needs to be transported to deep inland locations, across country borders. The increased peak generation capacity of renewable energy sources will, at times, significantly exceed demand (Matthew Langholtz, 2020). The traditional solution of continuously reinforcing and extending the electricity grid is not sustainable from a cost and societal perspective. This paper will, however, propose a deterministic approach on how networked (interconnected grid) Points of receipt (POR) to Points of Delivery (POD) can be optimized for wheeling renewable energy resources while minimizing energy cost with a hub and spoke approach. The statistical approach will be done via using existing daily energy market clearing prices, available transmission capacity and firm daily transmission prices in open access energy markets. Renewable energy targets, including specific offshore wind targets, need to be in line with the ramp-up as implied by the Paris Agreement. These targets are required to provide industry with a secure market outlook that allows them to build up supply chains accordingly. Optimizing wheeled energy paths from carbon neutral resources such as renewables make them not only cost competitive on the unit commitment stack, but also more accessible on the dispatch stack to other carbon heavy forms of generation such as coal and natural gas turbines (Matthew Langholtz, 2020). This correlates to maximizing renewable resource inertia (wind, solar, biomass) within an interconnected grid without having to consider additional expansion of resources via land purchases and de-forestation.