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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Status Report for Development of Advanced Process Monitoring Concepts for IAEA Safeguards Sponsored by the Next Generation Safeguards Initiative (NGSI)

Process monitoring (PM) is used in international safeguards as an additional measure to nuclear material accountancy (NMA). For large throughput nuclear facilities such as commercial spent fuel reprocessing plants, it is difficult to satisfy the lAEA's goal for detection probability using NMA alone. And, for an facilities, regardless of their throughput, PM can provide redundant verification for both NMA and containment and surveillance and can be used to detect abnormal plant operation through the use of IAEA's instrumentation and selected operator's process control instrumentation. Examples of PM include (1) continuity of knowledge of nuclear material flows and inventories by monitoring of tank solution levels in reprocessing plants, (2) load cell monitoring of cylinders in GCEPs, (3) thermal power monitoring of large research reactors to detect undeclared operation, and (4) providing data to enable frequent NMA-like evaluation (near-real-time-accounting), which involves a hybrid of NMA and PM, for many facility types. Sensors required for PM include for example sensors for measuring flow, volume, density, level, temperature, and other diverse sensors such as portal monitors, video cameras, motion detectors, and gamma and neutron detectors. Additionally, PM lends itself to remote and/or unattended monitoring which has the potential to reduce the IAEA inspection burden and intrusiveness to the operator.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2012

Solid-State Photomultiplier Development for Radiation Detection

We are pursuing the sensitivity of back-thinned silicon (BT Si) with the gain of an SSPM (Baker 2011). Working in collaboration with Radiation Monitoring Devices, Inc., we are designing and fabricating prototype devices. Our original idea spurred from hybrid designs of advanced image sensors that use the sensitivity of BT Si that is then bump bonded to a CMOS readout device. As shown in the graph below (right), the BT Si has a far superior quantum efficiency (QE) than the standard photocathode response available in photomultiplier tubes (PMTs). Collecting as many scintillation photons as possible is the first objective. There has been major concern that the prototype could not deliver the ~105 electronic gain of a PMT. However, recently developed SSPMs do provide the electronic gain needed. We are now pursuing the design of a BTSSPM. With a smaller footprint, the SSPM can potentially lead to a simple, compact deployment package. Because the SSPM can be pixelated and tiled, we foresee developing an imaging detector. Pinhole imaging of radiation sources is a well-exercised technology. Our implementation of the coded aperture (Marks 2010) imager provides a high throughput pinhole imager. We intend to apply miniature coded apertures to minimal pixel count SSPMs to evaluate image quality.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

A Graph Neural Network Surrogate Model for hls4ml

Recent advancements in use of machine learning (ML) techniques on field-programmable gate arrays (FPGAs) have allowed for the implementation of embedded neural networks with extremely low latency. This is invaluable for particle detectors at the Large Hadron Collider, where latency and used area are strictly bounded. The hls4ml framework is a procedure that converts trained ML model software to a synthesis result to can be used on an FPGA. However, running the pipeline is a time-consuming procedure, and there is a strong risk of failure. In particular, it may not be possible to successfully convert a model into a synthesis result, or the resource consumption of the model may exceed the resources of the target FPGA. To aid with this development, we introduce wa-hls4ml, a surrogate model using a graph neural network to emulate the structure of the source models. The goal is to estimate the chance of success and resource consumption of a given model when passed through the hls4ml pipeline, without needing to run the pipeline.

Plotnikov, Dennis↗
DOE OSTI2023

Cycle-by-cycle Delay Estimation at Signalized Intersections by using Machine Learning and Simulated Video Detection Data

Accurate estimation of delay is crucial for efficient traffic signal operations. Estimation of delay in the real-time manner using traditional loop detectors requires advanced detectors (in addition to stop-bar detection). In cases when this detection layout is not in place, delay estimates are approximated with a lower accuracy. Video detection is one of the most frequently deployed detection systems at signalized intersections in recent years. In most cases video detection operates in the same way as traditional inductive loops. However, when coupled with computer vision algorithms, video detection systems could be used to retrieve additional information (e.g., vehicular arrivals and departures) that cannot be taken out from the conventional systems (e.g., long stop-bar loop detectors). Although present for several decades, video detection data were not frequently examined for delay estimation purposes. In this study, we proposed a novel delay estimation model which can be developed with only data from stop-bar video detectors. Relevant data were collected from a simulation model of 11 signalized intersections at downtown Chattanooga, TN and processed to create needed inputs for model development. With the use of multigene genetic programming the authors developed a delay model that outperforms accuracy of multi regression model. Furthermore, authors evaluated the developed model by comparison with the other benchmark delay models, such as HCM and approach delay model. It was found that the developed MGGP delay model outperforms benchmark models for a wide range of traffic and signal operation conditions.

Erdagi, Ismet Goksad↗
DOE OSTI2018

Single Nanocrystal Spectroscopy of Shortwave Infrared Emitters

Short-wave infrared (SWIR) emitters are at the center of ground-breaking applications in biomedical imaging, next-generation optoelectronic devices, and optical communications. Colloidal nanocrystals based on indium arsenide are some of the most promising SWIR emitters to date. However, the lack of single-particle spectroscopic methods accessible in the SWIR has prevented advances in both nanocrystal synthesis and fundamental characterization of emitters. In this paper, we demonstrate an implementation of a solution photon correlation Fourier spectroscopy (s-PCFS) experiment utilizing the SWIR sensitivity and time resolution of superconducting nanowire single-photon detectors to extract single-particle emission linewidths from colloidal indium arsenide/cadmium selenide (InAs/CdSe) core/shell nanocrystals emissive from 1.2 to 1.6 μm. We show that the average single InAs/CdSe nanocrystal fluorescence linewidth is, remarkably, as narrow as 52 meV, similar to what has been observed in some of the most narrowband nanostructured emitters in the visible region. Additionally, the single nanocrystal fluorescence linewidth increases with increasing shell thickness, suggesting exciton–phonon coupling as the dominant emission line-broadening mechanism in this system. The development of the SWIR s-PCFS technique has enabled measurements of spectral linewidths of colloidal SWIR-emissive NCs in solution and provides a platform to study the single NC spectral characteristics of SWIR emitters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

New Radiological Material Detection Technologies for Nuclear Forensics: Remote Optical Imaging and Graphene-Based Sensors

We developed new detector technologies to identify the presence of radioactive materials for nuclear forensics applications. First, we investigated an optical radiation detection technique based on imaging nitrogen fluorescence excited by ionizing radiation. We demonstrated optical detection in air under indoor and outdoor conditions for alpha particles and gamma radiation at distances up to 75 meters. We also contributed to the development of next generation systems and concepts that could enable remote detection at distances greater than 1 km, and originated a concept that could enable daytime operation of the technique. A second area of research was the development of room-temperature graphene-based sensors for radiation detection and measurement. In this project, we observed tunable optical and charged particle detection, and developed improved devices. With further development, the advancements described in this report could enable new capabilities for nuclear forensics applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

wa-hls4ml: A GNN Surrogate Model for hls4ml

Recent advancements in use of machine learning techniques on field-programmable gate arrays (FPGAs) have allowed for implementation of embedded neural networks with extremely low latency. This is invaluable for particle detectors at the Large Hadron Collider, where latency and used area must be strictly bounded. The hls4ml framework is a procedure for converting from trained machine learning model software, to a synthesis result that can be used on an FPGA. However, running the pipeline is a time-consuming procedure, and there is a strong risk of failure. In particular, it is possible that the model is unable to be converted into a synthesis result, or that the resource consumption of the model will exceed the resources of the target FPGA. To aid with this development, we introduce wa-hls4ml, a surrogate model which uses a graph neural network to emulate the structure of the source models. The goal is to estimate the chance of success and resource consumption of an arbitrary model when passed through the hls4ml procedure, without the time consumption of actually running the pipeline.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Decay of the proton-unbound superradiant state in 13 N

Here, the 12 C ( 3 He, 𝑑)⁢ 13 N* reaction is studied in an experiment with a high-resolution magnetic spectrograph, in coincidence with protons detected in silicon detectors near the target. This allows for the observation of angular correlation patterns between the proton transfer and proton decays from populated unbound resonances. A formalism describing the spin polarization of direct reactions is developed to analyze these correlations, and is verified on the known directionally asymmetric decay distributions arising from parity mixing in the 13 N ⁡($\frac{3}{2}$ − , $\frac{5}{2}$ + ) doublet. The same formalism is used to study the decays from the continuum-aligned, broad 3/2 + resonance at 7.9 MeV excitation energy, which arises from superradiant coupling. The observed asymmetric angular correlation patterns are approximately reproduced by adding an “artificial” 3/2 − resonance with strength equal to that of the reaction formalism. This parity-mixing approach serves as a first approximation to a more advanced reaction model of rapid reaction and decay sequences.

13N↗
DOE OSTI2025

Resonant metasurface‐enabled quantum light sources for single‐photon emission and entangled photon‐pair generation

Light encodes information in multiple degrees of freedom (e.g., frequency, amplitude, and phase), enabling high‐speed, high‐bandwidth communication through fiber optics. Unlike classical light, quantum light (single or entangled photons) can transmit quantum states over long distances without loss of coherence, thereby coherently interconnecting quantum nodes for distributed quantum entanglement. Quantum light sources are critical for developing scalable quantum networks aimed at distributed quantum computing, quantum teleportation, and secure quantum communications. However, existing quantum light sources suffer from limited integrability, insufficient spectral and spatial tunability, and inefficiencies in achieving mass‐produced, deterministic, on‐demand quantum light generation. These limitations significantly hinder progress toward direct, on‐chip integration with quantum processing units and detectors – an essential step toward scalable quantum networks. Resonant metasurfaces that leverage photonic modes – such as Mie resonances, guided‐mode resonances, or symmetry‐protected bound states in the continuum – offer strong spatial and temporal confinement of electromagnetic fields, characterized by high quality factors and small mode volumes. These metasurfaces greatly enhance linear and nonlinear light‐matter interactions, making them ideal for efficient on‐chip quantum light generation and manipulation. Here, we describe recent advances in nanoscale quantum light sources and quantum photonic state manipulation enabled by resonant metasurfaces. We also provide an outlook on next‐generation miniaturized quantum light sources achievable through materials innovations in quantum emitters, the co‐design of resonant metasurfaces, and ultimately, the heterogeneous integration of emerging layered van der Waals materials with resonant metasurfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Development of MCNP Training Modules for Safeguards Practitioners [Abstract]

The Monte-Carlo N-Particle (MCNP) software developed at LANL is the most widely used neutron transport code in the world. It is an essential tool for a variety of applications including detector development and design, nuclear fuel burnup simulation, criticality safety, and nondestructive assay system optimization. For this reason, it is indispensable within the safeguards and materials control & accountability (MC&A) communities. Multiple MCNP training courses have been created and taught over the last several decades by the MCNP development team at LANL, however there are no existing courses that cover specialized topics considered fundamental to NDA and safeguards models. To fill this gap, the MCNP team and Safeguards Science and Technology group at LANL have co-created a set of training modules customized to meet the specialized needs of the safeguards and MC&A communities. The basic modules cover concepts such as NDA system optimization, He-specific and other capture tallies, and tools for improved theoretical understanding. An advanced module was also created to cover topics including variance reduction for active interrogation simulations, use of the LANL MCNPTools post-processor, PTRAC (particle tracking) and list-mode data simulations, and fuel burnup simulations. The training modules teach to the latest and most state-of-the-art MCNP features and tools released by the development team at LANL and are intended to be taught jointly by the developers and safeguards experts. Ultimately, we hope that creation of these modules will serve to capture and convey the safeguards modeling and MCNP expertise at LANL, and that we will be able to share the modules more broadly with the MC&A and safeguards communities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Optimizing microfluidic flow cell geometry for in situ resonant soft X-ray characterization of molecular nanostructures

Liquid-phase resonant soft X-ray scattering (LP-RSoXS) is an emerging label-free technique to probe chemically resolved nanostructures of molecular or hybrid materials in liquid environments. Still, quantitative analysis is hindered by the pressure-induced deformation of thin silicon nitride (SiN) membranes used as windows in microfluidic flow cells, which attenuates the signal in nonlinear ways, making experimental optimization difficult. Here, in this work, we directly characterize this deformation under experimental conditions for a variety of cell configurations. We use this to develop a predictive model that combines transmission effects of SiN bowing, incident X-ray beam profiles, and material-dependent resonant scattering cross sections to simulate the effective scattering intensity at the detector across the carbon K-edge. Maps of the total signal across the flow cell window reveal that increasing the window width and polymer concentration shifts the anisotropic intensity distributions from the center toward the edges of the window. It was determined that an optimal SiN thickness of 50 nm, with a window aperture of 104 μm, maximizes the total signal for typical solute concentrations and energies across the carbon K-edge. Our results overturn the assumption that corner regions dominate the scattering signal, offering explicit design guidelines for maximizing LP-RSoXS signals and significantly advancing the quantitative application of this technique to the characterization of molecular and hybrid nanostructured materials in liquids.

Grabner, Devin [Washington State Univ., Pullman, W↗
DOE OSTI2022

H2@Scale Program Multi-Party Cooperative Research and Development Agreement: California Hydrogen Infrastructure Research Consortium Task (Cooperative Research and Development Final Report, CRADA Number CRD-18-00754)

Many stakeholders are working on hydrogen and fuel cell products, markets, requirements, mandates, and policies. California has been leading the way for hydrogen infrastructure and fuel cell electric vehicle (FCEV) deployment. This leadership has advanced a hydrogen network that is not duplicated anywhere in the United States and is unique in the world for its focus on providing a retail fueling experience. In addition, the advancements have identified many lessons learned for hydrogen infrastructure development, deployment, and operation. Other interested states and countries are using California's experience as a model case, making success in California paramount to enabling market acceleration and uptake in the United States. The technical research capability of the national laboratories can be used to assist California in decisions and evaluations, as well as to verify solutions to problems impacting the industry. Because these challenges cannot be addressed by one agency or one laboratory, a hydrogen research consortium has been organized to combine and collaborate. The collaboration aims to ensure that data are available to evaluate projects and inform decision makers, independently verify and validate component solutions, provide experimental results for future hydrogen infrastructure, increase the availability of technical experts for quick-need issues for California hydrogen infrastructure development, deployment, operation, and technology advances. The proposed tasks include data collection from operational stations, component failure fix verification (i.e. nozzle freeze lock), new fueling methods for medium and heavy duty applications, and ensuring hydrogen quality is maintained. U.S. leadership for hydrogen technologies is rooted in California, a location for implementing many H2@Scale pathways such as reducing curtailment and stranded resources, reducing petroleum use and emissions, and developing and creating jobs.

08 HYDROGEN↗
DOE OSTI2024

Deep probabilistic direction prediction in 3D with applications to directional dark matter detectors

Abstract We present the first method to probabilistically predict 3D direction in a deep neural network model. The probabilistic predictions are modeled as a heteroscedastic von Mises-Fisher distribution on the sphere S 2 , giving a simple way to quantify aleatoric uncertainty. This approach generalizes the cosine distance loss which is a special case of our loss function when the uncertainty is assumed to be uniform across samples. We develop approximations required to make the likelihood function and gradient calculations stable. The method is applied to the task of predicting the 3D directions of electrons, the most complex signal in a class of experimental particle physics detectors designed to demonstrate the particle nature of dark matter and study solar neutrinos. Using simulated Monte Carlo data, the initial direction of recoiling electrons is inferred from their tortuous trajectories, as captured by the 3D detectors. For 40 keV electrons in a 70% He 30% CO 2 gas mixture at STP, the new approach achieves a mean cosine distance of 0.104 (26 ∘ ) compared to 0.556 (64 ∘ ) achieved by a non-machine learning algorithm. We show that the model is well-calibrated and accuracy can be increased further by removing samples with high predicted uncertainty. This advancement in probabilistic 3D directional learning could increase the sensitivity of directional dark matter detectors.

Computer Science↗
DOE OSTI2023

Analysis of WIRE-21 SPND and Optical Fiber Sensor Measurements

The Wireless Instrumented RB Experiment 2021 (WIRE-21) was a highly instrumented experiment designed to test prototype wireless temperature and pressure sensors developed by Westinghouse Electric Corporation (WEC) in the High Flux Isotope Reactor (HFIR). In addition to these sensors, a suite of other sensors was also integrated into the experiment capsule, including various types of distributed optical fiber sensors and self-powered neutron detectors (SPNDs). This report presents an analysis of the data generated by the SPNDs and optical fiber sensors that were tested under the highest reported neutron flux. The distributed optical fiber sensor results demonstrate that F-doped optical fibers, particularly those inscribed with fs fiber Bragg gratings (FBGs), are capable of surviving fast neutron fluences on the order of 1021 n fast /cm 2 at temperatures relevant to light-water reactors (between 200 and 400°C). However, a significant blue-shift in the optical spectra of these sensors was observed over the course of irradiation which cannot be explained based on the current understanding of radiation-induced compaction in fused silica glass. A mechanistic understanding of this drift has not yet been developed and is proposed as future scope under the Advanced Sensors and Instrumentation program. Of the four SPNDs, only one appeared to operate normally during three cycles of irradiation. A radiation transport model of the experiment in HFIR was used to determine time-dependent neutron flux in this SPND and to calculate the neutron sensitivity of the device. Results showed a cycle averaged sensitivity of 1.5 ×10 -22 and 1.4 ×10 -22 A/nν for the first and third cycles of irradiation, respectively. Additional details pertaining to the optical fibers and SPNDs are included herein.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Diagnostics: Chapter 8 of the special issue: on the path to tokamak burning plasma operation

This chapter presents the activity conducted by the ITPA topical group (TG) on Diagnostics over about the last 15 years. Following a general introduction of the ITER Diagnostics led by their measurement roles, the document is organized in several subchapters detailing the design support, research and development activity conducted by each of the specialist working groups (WGs) of the TG. Please note that the magnetic diagnostics were supported at the TG without a specific WG. Their status is included in the general introduction. In the following some highlights of the subchapter’s contents are provided. Recent advances in ITER first wall (FW) diagnostics for the measurements of plasma-metallic wall interaction in support of the ITER research plan are reported. An InfraRed imaging Video Bolometer for ITER has been developed and tested on several tokamaks to measure the radiated power loss. A laser-induced breakdown spectroscopy (LIBS) technique which utilizes a pulsed laser beam to ablate locally by forming a crater, will measure local tritium inventory in the FW material. Real-time Residual Gas Analyzers will measure the neutral gas composition in a divertor port and an equatorial port during plasma operation. Due to the full metallic FW environment, the plasma-wall interaction in ITER will face several challenges such as the compromised radiated power and divertor heat flux measurements by reflection. Ray tracing and analysis codes have been developed to eliminate and correct the effects of reflection in the measurements. The characteristics of the reflecting surfaces depending on the roughness and angle of the incidence have been measured by dedicated experiments, and the results were applied to the reflection elimination. For the measurement of the metallic impurity radiation induced by eroded metallic atoms, a vacuum ultraviolet spectrometer has been developed and tested. An extensive thermonuclear diagnostic suite will be required to support the operation of ITER and the planned experimental program for future burning plasma experiments. Due to the harsh environmental conditions, the implementation of diagnostic systems in ITER is a major challenge. These conditions include high levels of neutron and gamma fluxes, neutron heating, particle bombardment. Therefore, the selection and design of diagnostic systems must take into account a number of phenomena previously unseen in diagnostic design. For this reason, the measurement of neutrons and confined or lost fast ions, with particular emphasis on alpha particles, is critical to ITER. The diagnostics associated with these measurements will be important for future plasma-burning experiments at ITER. The high neutron emission and very large plasma size in ITER make neutron diagnostics the main diagnostic method used to measure plasma parameters such as fusion power, fusion power density, ion temperature, energy of fast ions and their spatial distributions in the plasma core. Active spectroscopy techniques are methods where a neutral particle beam is injected into the plasma and information on plasma parameters is extracted from the measurement of line emission resulting from the beam-plasma interaction, either by plasma ions or by beam atoms. Spatial localization is achieved by crossing the beamline and multiple observation lines. The ITER plasma will be a high temperature, moderately dense, fully ionized collisional plasma. The plasma facing surfaces are principally metallic being fashioned from beryllium or tungsten but many other elements, arising from either structural or from operational needs, may enter this plasma. The energy range of the emitted photons range from meV (infra-red) to multi keV (x-rays) and originate from all areas of the plasma volume. The primary role of passive emission diagnostics is to identify what is in the plasma from spectral signatures. Extracting quantitative information from these measurements such as impurity content, ion temperature, rotation, degree of detachment and radiated power depends on calibrated instruments, a physics model of the atomic and molecular processes and plasma transport and an analysis workflow that takes into account environmental effects such as reflections. The particular needs for ITER have prompted a multi-machine, many-year effort to address all these aspects and this chapter reviews the work on diagnostic design, experiments and new analysis techniques. An overview of the laser diagnostics to be implemented on ITER is also provided in this paper. This includes descriptions of the Thomson scattering in the core, edge and divertor regions, polarimetry and interferometry diagnostics used for measuring plasma density and also measurements of helium density in the divertor using Laser Induced Flourescence. Techniques which can allow improvements on current measurements are also addressed in particular expanding poloidal polarimetry measurements to measure field fluctuations and proposed use of dispersion interferometery which has a number of advantages over existing methods. This paper identifies particular areas where further research and testing on existing tokamaks is useful even at this advanced stage to inform the design of diagnostics for ITER. Outstanding areas of concern for the implementation of laser diagnostics, in particular with a view to reliable operation are identified. An overview of the latest developments of microwave diagnostic systems and techniques is given. The primary focus is the contributions for ITER—the next step burning plasma experiment—which is supplemented by describing recent progress of techniques applicable for fusion experiments beyond ITER. The contributions are intentionally kept concise, and are being supplemented by a rich list of references for further studies. Radiation induced effects are receiving continuous and well-deserved attention of the ITER diagnostic community and they are in many cases one of the primary design drivers of the ITER diagnostic systems. The paper summarizes recent progress in this area focusing primarily on the ITER diagnostics but in some cases provides also outlook for the possible solutions for even more demanding radiation environment of fusion reactors beyond ITER. Despite advancements in the area of modeling and simulation of various radiation induced effects, experimental testing in a nuclear environment as close as possible to the target one is still seen as unavoidable for proper qualification of particular diagnostic functional elements. Recent advancement within three diagnostic areas: optical diagnostics, magnetics and bolometers is covered. Encouraging results on qualification of silica glass vacuum window assemblies are presented. In the area of magnetic sensors, progress of irradiation tests performed on ITER in-vessel LTCC inductive sensors is presented with outlook for novel technological approaches to inductive sensors utilizing thick printing and photolithography technologies being highlighted. Summary of advancements in the area of steady state magnetic field sensors based on Hall effect is given. New results of neutron irradiation test of the ITER borosilicate glass inserts for vacuum electrical feedthroughs are summarized finding negligible swelling at target level of neutron fluence. Off-line irradiation tests of fiber optic current sensors for plasma current measurement demonstrated that both for gamma doses up to 5 MGy and a total neutron fluence up to 10 15 cm −2 , radiation induced changes are still compatible with required measurement accuracy on ITER. The ITER bolometers are given as an example how considering radiation effects may influence the diagnostic design. Finally, outlook for future main R&D directions is outlined. All optical and laser-based diagnostics in ITER will be using mirrors to guide plasma radiation toward detectors, cameras and sensors. In the hostile plasma, radiation and particle environment the optical characteristics of diagnostic mirrors will degrade directly affecting the entire performance of involved diagnostic systems. An assessment of factors affecting mirror performance is provided. Among the prime adverse factors are deposition of plasma impurities, sputtering of mirror surface and steam ingress in the vicinity of mirrors. Within the International Tokamak Physics Activity with active support by ITER central team and domestic agencies, the structured research and development (R&D) program on mitigation of risks for diagnostic mirrors is underway. Within this program the mirror material development, the passive mitigation of mirror degradation by using diagnostic ducts and shutters along with an active mirror recovery program comprising the in-situ mirror cleaning and calibration is underway. Recent developments in diagnostic mirror R&D are described in this Chapter along with an example of their implementation of R&D solutions in ITER Infrared Thermography diagnostic. An assessment of still open engineering and physics questions, considerations on mirror risks during an early phase of ITER operation are given along with an overview of diagnostic mirror evolution in the late ITER operation stage toward the demonstration fusion power plant. Several crucial areas of diagnostic R&D outlined in ITER Research Plan are addressed. The basic control groups in a fusion reactor can be broken-down in five categories: (1) plasma position, magnetic configuration, and plasma current control, (2) profile control and confinement optimization, (3) MHD control and suppression, (4) edge dissipation control, radiation and plasma exhaust control and (5) break-down optimization. These categories are coupled via the physics (a control action in one domain will affect the other domains) and via shared actuators (e.g. ECRH for impurity accumulation avoidance, current density distribution control and MHD suppression). Consequently, a supervisory control system should determine the priority of the various control tasks, their couplings, and the interfaces with the safety and interlock system. For the systematic development of the various controllers taking the complexity of the plasma and the control system into account, a model-based approach is required. A short historical overview is given of the developments in systems and control theory and control engineering with special emphasis on those developments that are most relevant for Nuclear Fusion research and operation. An overview is given of the state of the field of fusion plasma control for the control categories. It will be shown how synthetic diagnostics are being developed in ITER and how they are used in diagnostic design and design validation and how they can be in model-based controller synthesis using relatively simple models. In modern control methods, multiple diagnostics are used to constrain relatively simple models. The constrained models provide an estimate for the state. This opens the route to state controllers, such as model predictive control. A major challenge in nuclear fusion research is the coherent combination of data from heterogeneous diagnostics and modeling codes for machine control and safety as well as physics studies. Measured data from different diagnostics often provide information about the same subset of physical parameters. Additionally, information provided by some diagnostics might be needed for the analysis of other diagnostics. A joint analysis of complementary and redundant data allows, e.g. to improve the reliability of parameter estimation, to increase the spatial and temporal resolution of profiles, to obtain synergistic effects, to consider diagnostics interdependencies and to find and resolve data inconsistencies. Physics-based modeling and parameter relationships provide additional information improving the treatment of ill-posed inversion problems. A coherent combination of all kind of available information within a probabilistic framework allows for improved data analysis results. The concept of integrated data analysis (IDA) in the framework of Bayesian probability theory is outlined and contrasted with conventional data analysis. Components of the probabilistic approach are summarized and specific ingredients beneficial for data analysis at fusion devices are discussed.

ITER↗
DOE OSTI2015

Accurate determination of segmented X-ray detector geometry

Recent advances in X-ray detector technology have resulted in the introduction of segmented detectors composed of many small detector modules tiled together to cover a large detection area. Due to mechanical tolerances and the desire to be able to change the module layout to suit the needs of different experiments, the pixels on each module might not align perfectly on a regular grid. Several detectors are designed to permit detector sub-regions (or modules) to be moved relative to each other for different experiments. Accurate determination of the location of detector elements relative to the beam-sample interaction point is critical for many types of experiment, including X-ray crystallography, coherent diffractive imaging (CDI), small angle X-ray scattering (SAXS) and spectroscopy. For detectors with moveable modules, the relative positions of pixels are no longer fixed, necessitating the development of a simple procedure to calibrate detector geometry after reconfiguration. We describe a simple and robust method for determining the geometry of segmented X-ray detectors using measurements obtained by serial crystallography. By comparing the location of observed Bragg peaks to the spot locations predicted from the crystal indexing procedure, the position, rotation and distance of each module relative to the interaction region can be refined. Furthermore, we show that the refined detector geometry greatly improves the results of experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Gamma Spectroscopy Detector Candidates and Radioisotope Identification Algorithms for Use in National Security Applications

In 2006, the United States Congress mandated for the Department of Homeland Security (DHS) to screen all cargo containers to protect against terrorist acts and ensure the safety and security of the nation. Containers are screened by gamma and neutron detectors to ensure threat material is not smuggled into the country. However, because commerce is radioactive, detecting the presence of radioactive materials is not sufficient in ensuring the safety and security of the nation. Radioactive materials must also be identified in real time, thus distinguishing threat sources (Uranium-235 and Plutonium-230) from non-threat sources (kitty litter, pot ash, medical isotopes). Screening cargo containers can be considered a two-step process (1) alerting to the presence of radioactive material when gamma counts exceed a threshold setting, and (2) once alerted, identifying the type of radioactive material, which is done by collecting a gamma spectra and analyzing it with an analysis tool/algorithm. For this reason, it is important to evaluate not only emerging technology in neutron and gamma detection, but also investigate new advances in algorithm development for radioisotope identification (RIID). New candidates in detection and on-board algorithm analysis might offer opportunities to make the scanning, detection, and identification process more efficient while still ensuring the health and safety of the public. This research will investigate emerging technology in radiation detection focused on gamma spectroscopy capabilities and RIID algorithms for DHS applications.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

WE-AB-BRB-06: A Temperature Independent Plastic Scintillation Detector Capable of Simultaneous Dose and Temperature Measurement

Purpose: To evaluate a measurement method that renders plastic scintillation detectors temperature independent and capable of recovering dose and temperature information simultaneously. Methods: A novel approach was developed to account for the temperature dependence of plastic scintillation detectors (PSDs) without prior knowledge of the temperature. To enable this, the optical response of the scintillating element is separated into two sub-components, one being the response at a given temperature and the other accounting for the change in the optical emission spectrum with temperature. Using a previously demonstrated hyperspectral approach and following the proper calibration protocol, the contribution to scintillator emission and physical value of both dose and temperature can be obtained in real-time. To validate the method, dose and temperature were measured under cobalt irradiation in a temperature controlled water tank developed for this study. The temperature was varied from 22°C to 42°C. Depth-dose curves were also obtained during irradiations from a linear accelerator, first maintaining the water at room temperature and then warming it to 40°C and letting it cool down naturally over the course of the second measurement. Results: Dose measurements delivered with the Co-60 unit showed an average relative difference to the expected value of (1.0±0.8)%, with a maximum difference of 2.3% over the entire range of temperatures. The measured temperatures using the PSD were all within 1°C of the expected values. The difference between room temperature and warmer depth dose measurements differed by only (1.2±0.4)%. The dosimeter showed to be accurate for temporal resolution down to 0.1s. Conclusion: The proposed method was shown to reliably correct for the temperature dependence of a PSD. Additionally, it makes it possible to assess the temperature at the point of measurement. These are significant advances in PSD technology, particularly in relation to real-time in vivo dosimetry. Part of this research was supported by the Odyssey Program at The University of Texas MD Anderson Cancer Center.

60 APPLIED LIFE SCIENCES↗