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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Computational Modeling to Limit the Impact Displays and Indicator Lights Have on Habitable Volume Operational Lighting Constraints

NASA has demonstrated an interest in improving astronaut health and performance through the installment of a new lighting countermeasure on the International Space Station. The Solid State Lighting Assembly (SSLA) system is designed to positively influence astronaut health by providing a daily change to light spectrum to improve circadian entrainment. Unfortunately, existing NASA standards and requirements define ambient light level requirements for crew sleep and other tasks, yet the number of light-emitting diode (LED) indicators and displays within a habitable volume is currently uncontrolled. Because each of these light sources has its own unique spectral properties, the additive lighting environment ends up becoming something different from what was planned or researched. Restricting the use of displays and indicators is not a solution because these systems provide beneficial crew feedback.

Clark, T. A.↗
NASA NTRS2018

Developing a Remotely Sensed Drought Monitoring Indicator for Morocco

Drought is one of the most serious climatic and natural disasters inflicting serious impacts on the socio-economy of Morocco, which is characterized both by low-average annual rainfall and high irregularity in the spatial distribution and timing of precipitation across the country. This work aims to develop a comprehensive and integrated method for drought monitoring based on remote sensing techniques. The main input parameters are derived monthly from satellite data at the national scale and are then combined to generate a composite drought index presenting different severity classes of drought. The input parameters are: Standardized Precipitation Index calculated from satellite-based precipitation data since 1981 (CHIRPS), anomalies in the day-night difference of Land Surface Temperature as a proxy for soil moisture, Normalized Difference Vegetation Index anomalies from Moderate Resolution Imaging Spectroradiometer (MODIS) data and Evapotranspiration anomalies from surface energy balance modeling. All of these satellite-based indices are being used to monitor vegetation condition, rainfall and land surface temperature. The weighted combination of these input parameters into one composite indicator takes into account the importance of the rainfall-based parameter (SPI). The composite drought index maps were generated during the growing seasons going back to 2003. These maps have been compared to both the historical, in situ precipitation data across Morocco and with the historical yield data across different provinces with information being available since 2000. The maps are disseminated monthly to several main stakeholders' groups including the Ministry of Agriculture and Department of Water in Morocco.

Drought monitoring↗
NASA NTRS2019

Introducing NASA Ames' New Infrared Optical Constant Facility. Determinations of Complex Refractive Indices for Titan Aerosol Analogs and Other Applications

A new optical constant facility has been developed at NASA Ames that will allow the determination of optical constants in the infrared of various materials, analogs of (exo)planetary hazes and cloud particles. Our facility is composed of a Fourier Transform Infrared (FTIR) spectrometer continuously covering the Near-IR to Far-IR range (from 0.74 to 200 μm), coupled to variable angle transmittance and reflectance accessories that allow the characterization of the scattering properties of non-homogeneous samples (laboratory (exo)planetary aerosol analogs, films, slabs of material, crystals, powders, etc.) over a wide incidence and emittance angle range (0-90 degrees). This new experimental setup allows the characterization of angular light distribution in both transmission and reflection measurements, and enables the determination of the complex indices of refraction, n and k, over the full NIR-FIR range via modeling of the laboratory measurements. The resulting refractive indices are critical input parameters in radiative transfer models, microphysical models, cloud models, protoplanetary disk simulations and other models used for the interpretation of observational data from past, current and future (exo)planetary NASA missions. Here we present a description of the facility along with the first determination of optical constants for Titan aerosol analogs produced in the Titan Haze Simulation (THS) experiment on COSmIC, a unique experimental setup developed at NASA Ames that allows the simulation of Titan’s complex atmospheric chemistry at Titan-like temperature (200 K). We also introduce a new study of the optical properties of ammonium-bearing phosphates, potential cloud particles forming in temperate exoplanets and brown dwarfs.

Sciamma-O'Brien, Ella M.↗
NASA NTRS2020

Building a landslide hazard indicator with machine learning and land surface models

The U.S. Pacific Northwest has a history of frequent and occasionally deadly landslides caused by various factors. Using a multivariate, machine-learning approach, we combined a Pacific Northwest Landslide Inventory with a 36-year gridded hydrologic dataset from the National Climate Assessment – Land Data Assimilation System to produce a landslide hazard indicator (LHI) on a daily 0.125-degree grid. The LHI identified where and when landslides were most probable over the years 1979–2016, addressing issues of bias and completeness that muddy the analysis of multi-decadal landslide inventories. The seasonal cycle was strong along the west coast, with a peak in the winter, but weaker east of the Cascade Range. This lagging indicator can fill gaps in the observational record to identify the seasonality of landslides over a large spatiotemporal domain and show how landslide hazard has responded to a changing climate.

XGBoost↗
NASA NTRS2020

Billion-year exposure ages in Gale crater (Mars) indicate Mount Sharp formed before the Amazonian period

The erosion rates and mechanisms operating on Mount Sharp in Gale crater, Mars were assessed via experiments performed by the SAM instrument to determine the cosmogenic noble gas contents of Murray mudstone formation samples Mojave 2 and Quela. Previous measurements of samples from the Aeolis Palus depression between Mount Sharp and the north rim of Gale crater indicate that scarp retreat-generated surfaces formed within the last 100 Ma. In contrast, Mojave 2 yielded exposure ages of 1,320±240 (3He), 910±420 (21Ne), and 310±60 Ma (36Ar). Quela gave a 3He age of 1,460±200 Ma; 21Ne and 36Ar from this sample could not be quantified due to isobaric interferences. The discordant and young 36Ar exposure age in Mojave 2 is likely the result of interaction with water which dissolved the chlorine-bearing host phases of this nuclide. The most probable exposure scenario is that both Mojave 2 and Quela have been at the surface for the most recent ∼1 Ga after the overlying few meters of rock were removed in a geologically rapid exhumation episode. Based on local geomorphology, scarp retreat is the most likely mechanism for the exposure at these two sites. The exposure ages measured throughout Curiosity’s traverse indicate that the net removal of rock has proceeded more recently on Aeolis Palus than on the lower slopes of Mount Sharp. The implied differential erosion rate is insufficient to explain how Mount Sharp formed, even over billions of years. Instead, given that the surfaces on Mount Sharp have existed for >1 Ga, the mountain must have formed early, likely during the Hesperian. This study provides direct quantitative support for inferences based on crater counts that Mount Sharp had eroded to close to its current form before onset of the Amazonian.

Peter E. Martin↗
NASA NTRSDate not supplied

Analyzing the Subjectivity of Hole-Type Image Quality Indicators for Radiography

Hole-type penetrameters used as image quality indicators (IQIs) for radiography have an inherent degree of subjectivity to their interpretation. The 1T (one times the thickness of the penetrameter) hole is so small, it can be difficult to distinguish from noise. It is suspected that an operator’s knowledge of the true location of the 1T hole may subconsciously influence a false positive identification of the 1T hole when in fact it cannot be discerned. In the case of computed radiography (CR), the size of the phosphor particles may lead to a noise pattern with features on the scale of the 1T hole. Per NASA-STD-5009, the 1T hole must be detected in order to achieve adequate sensitivity. This is based on the historical understanding that this sensitivity will enable detection of the minimum detectable flaw sizes listed in the standard. It’s important to understand if 1T sensitivity is being achieved, and the associated risk if not. This study sought to determine the true detectability of 1T-sized holes in aluminum and Inconel by creating and inspecting a set of penetrameters with randomly placed holes. Enough holes and vacant zones were created to enable a full probability of detection study with 90% detectability, 95% confidence. Testing is ongoing, but preliminary results have shown poor detectability. The detection rate is slightly better for Inconel than aluminum, slightly better using a micro-focus vs. mini-focus tube, and definitively better for film than CR. One of the key questions of this study is whether historical requirements for film are applicable for CR, and these initial findings suggest they may not be. There is also a requirement in the NASA standard for the minimum contrast-to-noise ratio of the hole. The results have shown that this numerical threshold does not correlate well with visual detection. This raises questions about the true nature of detection, in an age of image processing vs. human judgement. As the results indicate that the detection of 1T holes is unreliable, the next challenge will be determining what sensitivity is really achieved, and what is needed.

Erin Lanigan↗
NASA NTRS2021

Scaling photosynthetic function and CO2 dynamics from leaf to canopy level for maize – dataset combining diurnal and seasonal measurements of vegetation fluorescence, reflectance and vegetation indices with canopy gross ecosystem productivity

Recent advances in leaf fluorescence measurements and canopy proximal remote sensing currently enable the non-destructive collection of rich diurnal and seasonal time series, which are required for monitoring vegetation function at the temporal and spatial scales relevant to the natural dynamics of photosynthesis. Remote sensing assessments of vegetation function have traditionally used actively excited foliar chlorophyll fluorescence measurements, canopy optical reflectance data and vegetation indices (VIs), and only recently passive solar induced chlorophyll fluorescence (SIF) measurements. In general, reflectance data are more sensitive to the seasonal variations in canopy chlorophyll content and foliar biomass, while fluorescence observations more closely relate to the dynamic changes in plant photosynthetic function. With this dataset we link leaf level actively excited chlorophyll fluorescence, canopy proximal reflectance and SIF, with eddy covariance measurements of gross ecosystem productivity (GEP). The dataset was collected during the 2017 growing season on maize, using three automated systems (i.e., Monitoring Pulse-Amplitude-Modulation fluorimeter, Moni-PAM; Fluorescence Box, FloX; and from eddy covariance tower). The data were quality checked, filtered and collated to a common 30 minutes timestep. We derived vegetation indices related to canopy functioning (e.g., Photochemical Reflectance Index, PRI; Normalized Difference Vegetation Index, NDVI; Chlorophyll Red-edge, Clre) to investigate how SIF and VIs can be coupled for monitoring vegetation photosynthesis. The raw datasets and the filtered and collated data are provided to enable new processing and analyses.

Petya Campbell↗
NASA NTRS2022

Simultaneous Retrieval of Selected Optical Water Quality Indicators From Landsat-8, Sentinel-2, and Sentinel-3

Constructing multi-source satellite-derived water quality (WQ) products in inland and nearshore coastal waters from the past, present, and future missions is a long-standing challenge. Despite inherent differences in sensors’ spectral capability, spatial sampling, and radiometric performance, research efforts focused on formulating, implementing, and validating universal WQ algorithms continue to evolve. This research extends a recently developed machine-learning (ML) model, i.e., Mixture Density Networks (MDNs) (Pahlevan et al., 2020; Smith et al., 2021), to the inverse problem of simultaneously retrieving WQ indicators, including chlorophyll-a (Chla), Total Suspended Solids (TSS), and the absorption by Colored Dissolved Organic Matter at 440 nm (a cdom (440)), across a wide array of aquatic ecosystems. We use a database of in situ measurements to train and optimize MDN models developed for the relevant spectral measurements (400–800 nm) of the Operational Land Imager (OLI), MultiSpectral Instrument (MSI), and Ocean and Land Color Instrument (OLCI) aboard the Landsat-8, Sentinel-2, and Sentinel-3 missions, respectively. Our two performance assessment approaches, namely hold-out and leave-one-out, suggest significant, albeit varying degrees of improvements with respect to second-best algorithms, depending on the sensor and WQ indicator (e.g., 68%, 75%, 117% improvements based on the hold-out method for Chla, TSS, and a cdom (440), respectively from MSI-like spectra). Using these two assessment methods, we provide theoretical upper and lower bounds on model performance when evaluating similar and/or out-of-sample datasets. To evaluate multi-mission product consistency across broad spatial scales, map products are demonstrated for three near-concurrent OLI, MSI, and OLCI acquisitions. Overall, estimated TSS and a cdom (440) from these three missions are consistent within the uncertainty of the model, but Chla maps from MSI and OLCI achieve greater accuracy than those from OLI. By applying two different atmospheric correction processors to OLI and MSI images, we also conduct matchup analyses to quantify the sensitivity of the MDN model and best-practice algorithms to uncertainties in reflectance products. Our model is less or equally sensitive to these uncertainties compared to other algorithms. Recognizing their uncertainties, MDN models can be applied as a global algorithm to enable harmonized retrievals of Chla, TSS, and a cdom (440) in various aquatic ecosystems from multi-source satellite imagery. Local and/or regional ML models tuned with an apt data distribution (e.g., a subset of our dataset) should nevertheless be expected to outperform our global model.

Machine learning↗
NASA NTRS2022

Deuterium Isotope Fractionation of Polycyclic Aromatic Hydrocarbons in Meteorites as an Indicator of Interstellar/Protosolar Processing History

The stable isotope composition of soluble and insoluble organic compounds in carbonaceous chondrites can be used to determine the provenance of organic molecules in space. Deuterium enrichment in meteoritic organics could be a residual signal of synthetic reactions occurring in the cold interstellar medium or an indicator of hydrothermal parent-body reactions. δD values have been measured in grains and bulk samples for a wide range of meteorites; however, these reservoirs are highly variable and may have experienced fractionation during thermal and/or aqueous alteration. Among the plethora of organic compounds in meteorites are polycyclic aromatic hydrocarbons (PAHs), which are stable and abundant in carbonaceous chondrites, and their δD ratio may preserve evidence about their formation environment as well as the influence of parent-body processes. This study tests hypotheses about the potential links between PAHs-deuteration concentrations and their formation conditions by examining the δD ratio of PAHs in three CM carbonaceous chondrites representing an aqueous alteration gradient. We use deuterium enrichments in soluble 2–5-ring PAHs as an indicator of either photon-driven deuteration due to unimolecular photodissociation in warm regions of space, gas-phase ion–molecule reactions in cold interstellar regions of space, or UV photolysis in ices. We also test hypothesized reaction pathways during parent-body processing that differ between partially and fully aromatized PAHs. New methodological approaches were developed to extract small, volatile PAHs without fractionation. Our results suggest that meteoritic PAHs could have formed through reactions in cold regions, with possible overprinting of deuterium enrichment during aqueous parent-body alteration, but the data could not rule out PAH alteration in icy mantles as well.

H V Graham↗
NASA NTRS2022

A Rotation Procedure to Improve Seasonally Varying Empirical Orthogonal Function Bases for MJO Indices

Various indices have been defined to characterize the phase and amplitude of the Madden-Julian oscillation (MJO). One widely used index is the Outgoing Longwave Radiation (OLR) based MJO index (OMI), which is calculated using the spatial pattern of 30-96-day eastward-filtered OLR. The EOFs used to calculate the OMI in observations are prone to degeneracy and exhibit oscillations on the order of 10-20 days, despite initial filtering of the OLR. We propose a simple modification to the OMI that involves aligning the EOFs between neighboring days while retaining the spatial pattern described by the EOFs. This rotation method is implemented as a postprocessing procedure of the current OMI calculation and cleanly removes the spurious oscillations and degeneracy issues seen in the standard method. A similar rotation procedure can be implemented in calculations of other MJO indices.

Sarah Weidman↗
NASA NTRS2023

Vibration Anomaly Indicator in UAVs in presence of Wind

One of the critical factors affecting flight safety of unmanned aerial vehicles (UAVs) is the amount of vibration they are exposed during a flight. For UAVs under remote operation, vehicle stabilization and navigation is typically achieved by estimating its attitude and position using onboard miniature sensors such as accelerometers, gyroscopes, and GPS via an onboard autopilot. Since precise control of the UAV relies heavily on the attitude sensing, the vibration levels need to be as low as possible in order to minimize the signal noise. Incorrect sensor data can lead to uncertain state estimation causing the multirotor to drift from its desired position. Moreover, high vibrations can induce faults in the safety-critical components of the UAV such as its on-board sensors, motors and propellers. Hence, it is important to monitor the vibration levels during a UAV flight. This paper specifically looks into effect of wind on the vibrations recorded by the autopilot system in an octocopter. Using data from experimental flights under varying wind conditions, we aim to classify between a nominal and anomalous vibration level and define a safety metric known as the Vibrational Anomaly Indicator (VAI) for small UAV systems. Further, we will study effect of high vibrations on the inertial measurement unit (IMU) of an octocopter under laboratory set-up and compute the VAI from IMU measurements. Results would demonstrate the utility of VAI as an health indicator for unmanned flights either in presence of winds or from degraded on-board IMU sensor.

Vibration↗
NASA NTRSDate not supplied

Analyzing the Subjectivity of Hole-Type Image Quality Indicators for Radiography

Hole-type penetrameters used as image quality indicators (IQIs) for radiography have an inherent degree of subjectivity to their interpretation. The 1T (one times the thickness of the penetrameter) hole is so small, it can be difficult to distinguish from noise. It is suspected that an operator’s knowledge of the true location of the 1T hole may subconsciously influence a false positive identification of the 1T hole when in fact it cannot be discerned. In the case of computed radiography (CR), the size of the phosphor particles may lead to a noise pattern with features on the scale of the 1T hole. Per NASA-STD-5009, the 1T hole must be detected in order to achieve adequate sensitivity. This is based on the historical understanding that this sensitivity will enable detection of the minimum detectable flaw sizes listed in the standard. It’s important to understand if 1T sensitivity is being achieved, and the associated risk if not. This study sought to determine the true detectability of 1T-sized holes in aluminum and Inconel by creating and inspecting a set of penetrameters with randomly placed holes. Enough holes and vacant zones were created to enable a full probability of detection study with 90% detectability, 95% confidence. Testing is ongoing, but preliminary results have shown poor detectability. The detection rate is slightly better for Inconel than aluminum, slightly better using a micro-focus vs. mini-focus tube, and definitively better for film than CR. One of the key questions of this study is whether historical requirements for film are applicable for CR, and these initial findings suggest they may not be. There is also a requirement in the NASA standard for the minimum contrast-to-noise ratio of the hole. The results have shown that this numerical threshold does not correlate well with visual detection. This raises questions about the true nature of detection, in an age of image processing vs. human judgement. As the results indicate that the detection of 1T holes is unreliable, the next challenge will be determining what sensitivity is really achieved, and what is needed.

Erin Lanigan↗
NASA NTRSDate not supplied

A Comparative Study of Contrail Frequency Indices and GOES-16 Contrail Data Set

Contrail formations have been shown to contribute to the greenhouse effect: they are practically transparent to incoming solar radiation and do little to reflect heat away from Earth but are highly effective at trapping heat within Earth’s atmosphere. To understand the impact contrails have on climate change, contrail frequency indices (CFIs) can be used as a method to quantify aircraft-induced persistent contrails. These indices are capable of tracking long-term contrail formation and identify regions of airspace with the highest contrail formation rates. In this aper, an algorithm is proposed which is capable of using NASA Sherlock and Global Forecast System (GFS) datasets and computing CFIs over large geographic regions and long temporal intervals using NASA Ames’ High-End Computing Capability (HECC) supercomputing system. CFIs are computed using nowcast weather data and previously flown flight tracks. This paper calculated the CFIs of all twenty Air Route Traffic Control Centers in the National Airspace System on October 28th, 2019 and compared the distribution of non-zero CFIs with observed contrail data collected from GOES-16 Satellite data in order to assess the accuracy of the CFI system as a contrail prediction model. It was ultimately determined that the computed CFIs were broadly distributed in the same way as the GOES-16 contrail data and that the individual CFIs computed at the latitude/longitude points at which GOES-16 contrail masks were available had high precision and recall (at 0.75 and 0.86 respectively). While these validation results bode well for the accuracy of the CFI method, the number of provided GOES-16 masks was quite small. Future work should aim to increase the size of the GOES-16 dataset in order to perform a more comprehensive comparison between these two datasets.

Contrails↗
NASA NTRSDate not supplied

A Comparative Study of Contrail Frequency Indices and GOES-16 Contrail Data Set

Contrail formations have been shown to contribute to the greenhouse effect: they are practically transparent to incoming solar radiation and do little to reflect heat away from Earth but are highly effective at trapping heat within Earth’s atmosphere. To understand the impact contrails have on climate change, contrail frequency indices (CFIs) can be used as a method to quantify aircraft-induced persistent contrails. These indices are capable of tracking long-term contrail formation and identify regions of airspace with the highest contrail formation rates. In this aper, an algorithm is proposed which is capable of using NASA Sherlock and Global Forecast System (GFS) datasets and computing CFIs over large geographic regions and long temporal intervals using NASA Ames’ High-End Computing Capability (HECC) supercomputing system. CFIs are computed using nowcast weather data and previously flown flight tracks. This paper calculated the CFIs of all twenty Air Route Traffic Control Centers in the National Airspace System on October 28th, 2019 and compared the distribution of non-zero CFIs with observed contrail data collected from GOES-16 Satellite data in order to assess the accuracy of the CFI system as a contrail prediction model. It was ultimately determined that the computed CFIs were broadly distributed in the same way as the GOES-16 contrail data and that the individual CFIs computed at the latitude/longitude points at which GOES-16 contrail masks were available had high precision and recall (at 0.75 and 0.86 respectively). While these validation results bode well for the accuracy of the CFI method, the number of provided GOES-16 masks was quite small. Future work should aim to increase the size of the GOES-16 dataset in order to perform a more comprehensive comparison between these two datasets.

Contrails↗
NASA NTRSDate not supplied

Identifying Indicators of Harmful Algal Blooms in Coastal Atacama Using Satellite Image Processing Techniques to Improve Industry and Authority Response

Over the past decade, Chile has experienced a significant rise in both the frequency and intensity of coastal Harmful Algal Blooms (HABs). These bloom events are a growing concern for the Atacama Region especially, with potential impacts on human health, aquaculture, and the environment. HABs are caused by an excess proliferation of microalgae, with certain algae species commonly found in Chilean HABs capable of producing toxins which can poison fish, toxify shellfish, and cause illness or death when ingested by humans. Collaborating with the Ministry of Health of Chile, Centro de Información de Recursos Naturales, the University of Atacama, and the Embassy of Chile’s Agricultural Office, this study identifies potential indicators of HABs in the Coastal Atacama Region using NASA Earth observations. Satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard NASA’s Aqua satellite was used for the identification of chlorophyll-a which provides direct estimates of the algae pigment’s concentration in water bodies. In addition, the spatiotemporal patterns of several other parameters were examined to identify correlations with occurrences of HABs, including sea surface temperature and normalized fluorescence line height using Aqua MODIS, Normalized Difference Turbidity Index (NDTI) using Landsat 8, and ocean wind speed measurements from the NOAA Joint Polar Satellite System. Analysis of these patterns revealed hotspots of high chlorophyll-a concentrations from the years 2014 to 2022, the most major of which occurring in the coastal zones of Chañaral, Bahía Inglesa, and Huasco. Also, through the use of a similarity search conducted, the seasonal variation of these indicators was mapped to highlight areas with great likelihood of experiencing HABs in the future. The results can guide future efforts for in-situ water sampling, toxin analysis and assessment, and HAB monitoring and prevention.

Cody O'Ferrall↗
DOE OSTI2024

Review of Technical Photovoltaic Key Performance Indicators and the Importance of Data Quality Routines

Technical key performance indicators (KPIs) are important metrics used to assess and quantitatively summarize various aspects of photovoltaic (PV) systems, including long-term performance, economic viability, and carbon footprint. Herein, a group of experts of the International Energy Agency's Photovoltaic Power Systems Programme Task 13 collect and describ the most important technical KPIs used in the industry. Thereby, a set of best practices for reliably handling PV system data is presented and the impact of data quality and climatic variability on KPI calculation is investigated. Further, the effective use of technical KPIs allows triggering data-driven and informed decisions to optimize PV systems and providing a comprehensive overview of how PV systems operate across different conditions and climates. With the worldwide growth of the PV industry, more companies operate/own PV systems in different regions, where the climatic and seasonal profiles differ. This requires context-aware evaluation of KPIs, or the judicious application of multiple KPIs, to ensure that each asset is evaluated correctly. Beyond that, there is untapped potential in the utilization of KPIs through geospatial mapping and extrapolation of fleet KPIs. This study demonstrates that the uncertainty in KPI estimation is not well understood and depends on data quality, climatic variability, and system configuration.

14 SOLAR ENERGY↗
DOE OSTI2025

Test and Evaluation of Radiofrequency Tamper Indicating Devices for Remote Monitoring of Advanced/Small Modular Reactors

Advanced and small modular reactors (A/SMRs), due to their versatile nature, are likely to be used in remote locations to provide electrical power or other services in regions that are difficult to access or have limited transportation infrastructure. This will result in limited on-site staff, therefore driving A/SMR vendors to consider remote monitoring as a solution to support nuclear security. Maintaining Continuity of Knowledge (CoK) of nuclear material quantities and locations is vital to nuclear security, and remote monitoring of active tamper indicating devices (TIDs) has been well established as a component of International Atomic Energy Agency (IAEA) Safeguards since the early 2000s. Active TIDs, such as radiofrequency TIDs (RFTIDs), immediately alarm upon unauthorized access attempts, promoting timely detection. In contrast, passive TIDs require a surveillance regime and offer delayed detection. Active TIDs deter insiders and enable prompt detection of malicious acts. They can be used on nuclear material containers and controlled entry points like vaults and toolboxes. Therefore, the implementation of RFTIDs into security programs bolsters overall nuclear material control, and provides a visible deterrent, with primary efficacy in mitigating the insider threat and potentially allowing for Security by Design considerations. They are a strong candidate technology for maintaining nuclear security of A/SMRs but need to be evaluated for feasibility and implementation into the wider physical protection system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗