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At least 1,243 records · Page 69

Analytic variance estimates of Swank and Fano factors

Purpose: Variance estimates for detector energy resolution metrics can be used as stopping criteria in Monte Carlo simulations for the purpose of ensuring a small uncertainty of those metrics and for the design of variance reduction techniques. Methods: The authors derive an estimate for the variance of two energy resolution metrics, the Swank factor and the Fano factor, in terms of statistical moments that can be accumulated without significant computational overhead. The authors examine the accuracy of these two estimators and demonstrate how the estimates of the coefficient of variation of the Swank and Fano factors behave with data from a Monte Carlo simulation of an indirect x-ray imaging detector. Results: The authors' analyses suggest that the accuracy of their variance estimators is appropriate for estimating the actual variances of the Swank and Fano factors for a variety of distributions of detector outputs. Conclusions: The variance estimators derived in this work provide a computationally convenient way to estimate the error or coefficient of variation of the Swank and Fano factors during Monte Carlo simulations of radiation imaging systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-E-T-136: Dosimetric Robustness of a Magnetic Resonance Imaging Guided Radiation Therapy (MR-IGRT) System

Purpose: To test the radiation delivery robustness of the first MR-IGRT system using a commercial cylindrical diode array detector (ArcCHECK) and an ionization thimble chamber (Exradin A18). Methods: The MR-IGRT system is composed of three evenly spaced Co-60 sources on a rotating gantry located between two magnet halves. The collimator for each source consists of 30 doubly-focused leaf pairs that allow the system to deliver both conformal and intensity modulated (IMRT) treatment plans. The system's delivery robustness was tested over a span of 6 months from September 2013 through February 2014. This was achieved by repeatedly delivering 10 patient plans. These plans consisted of 2 conformal prostates, 2 IMRT prostates, 2 IMRT head and neck, 2 IMRT breast, 1 IMRT pancreas, and 1 IMRT bladder. The plans were generated with the system's treatment planning software. Once the plans were generated, quality assurance plans were created on a digital ArcCHECK dataset. The ArcCHECK used for testing was specially designed to be MR-compatible by moving the power supply outside of the magnetic field. The A18 ionization chamber was placed in a custom plastic plug insert in the center of the ArcCHECK. Gamma analysis was used with the ArcCHECK for relative dose evaluating both 3%/3mm and 2%/2mm. Absolute point dose was compared between ion chamber measurement and treatment plan. Results: The ArcCHECK passing rate remained constant over the 6 month period. The average passing rate for 3%/3mm and 2%/2mm analysis was 98.6% ± 0.7 and 88.8% ± 2.9, respectively. The ion chamber measurements showed little variation with an average percent difference between planned dose verses measured dose of 0.9% ± 0.7. Conclusion: Minimal differences were noted in the delivery of the 10 patient plans. Over a period that included acceptance testing, commissioning, and clinical deliveries, the MR-IGRT system remained consistent in radiation delivery.

60 APPLIED LIFE SCIENCES↗

SU-F-T-476: Performance of the AS1200 EPID for Periodic Photon Quality Assurance

Purpose: To assess the dosimetric performance of a new amorphous silicon flat-panel electronic portal imaging device (EPID) suitable for high-intensity, flattening-filter-free delivery mode. Methods: An EPID-based QA suite was created with automation to periodically monitor photon central-axis output and two-dimensional beam profile constancy as a function of gantry angle and dose-rate. A Varian TrueBeamTM linear accelerator installed with Developer Mode was used to customize and deliver XML script routines for the QA suite using the dosimetry mode image acquisition for an aS1200 EPID. Automatic post-processing software was developed to analyze the resulting DICOM images. Results: The EPID was used to monitor photon beam output constancy (central-axis), flatness, and symmetry over a period of 10 months for four photon beam energies (6x, 15x, 6xFFF, and 10xFFF). EPID results were consistent to those measured with a standard daily QA check device. At the four cardinal gantry angles, the standard deviation of the EPID central-axis output was <0.5%. Likewise, EPID measurements were independent for the wide range of dose rates (including up to 2400 mu/min for 10xFFF) studied with a standard deviation of <0.8% relative to the nominal dose rate for each energy. Also, profile constancy and field size measurements showed good agreement with the reference acquisition of 0° gantry angle and nominal dose rate. XML script files were also tested for MU linearity and picket-fence delivery. Using Developer Mode, the test suite was delivered in <60 minutes for all 4 photon energies with 4 dose rates per energy and 5 picket-fence acquisitions. Conclusion: Dosimetry image acquisition using a new EPID was found to be accurate for standard and high-intensity photon beams over a broad range of dose rates over 10 months. Developer Mode provided an efficient platform to customize the EPID acquisitions by using custom script files which significantly reduced the time. This work was funded in part by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

SU-G-JeP3-10: Update On a Real-Time Treatment Guidance System Using An IR Navigation System for Pleural PDT

Purpose: Photodynamic therapy (PDT) is used in conjunction with surgical debulking of tumorous tissue during treatment for pleural mesothelioma. One of the key components of effective PDT is uniform light distribution. Currently, light is monitored with 8 isotropic light detectors that are placed at specific locations inside the pleural cavity. A tracking system with real-time feedback software can be utilized to improve the uniformity of light in addition to the existing detectors. Methods: An infrared (IR) tracking camera is used to monitor the movement of the light source. The same system determines the pleural geometry of the treatment area. Software upgrades allow visualization of the pleural cavity as a two-dimensional volume. The treatment delivery wand was upgraded for ease of light delivery while incorporating the IR system. Isotropic detector locations are also displayed. Data from the tracking system is used to calculate the light fluence rate delivered. This data is also compared with in vivo data collected via the isotropic detectors. Furthermore, treatment volume information will be used to form light dose volume histograms of the pleural cavity. Results: In a phantom study, the light distribution was improved by using real-time guidance compared to the distribution when using detectors without guidance. With the tracking system, 2D data can be collected regarding light fluence rather than just the 8 discrete locations inside the pleural cavity. Light fluence distribution on the entire cavity can be calculated at every time in the treatment. Conclusion: The IR camera has been used successfully during pleural PDT patient treatment to track the motion of the light source and provide real-time display of 2D light fluence. It is possible to use the feedback system to deliver a more uniform dose of light throughout the pleural cavity.

60 APPLIED LIFE SCIENCES↗

TH-AB-207A-04: Assessment of Patients’ Cumulative Effective Dose From CT Examinations

Purpose: The Joint Commission requires institutions to consider patient’s age and recent imaging exams when deciding on the most appropriate type of imaging exam. Additionally, knowing patient’s imaging history can help prevent duplicate scans. Radiation dose management software affords new opportunities to identify and utilize patients with high cumulative doses as one proxy for subsequent review of imaging history and opportunities in avoiding redundant exams. Methods: Using dose management software (Radimetrics, Bayer Healthcare) a total of 72073 CT examinations performed from Jan 2015 to Jan 2016 were examined to categorize patients with a cumulative effective dose of 100 mSv and above. This threshold was selected based on epidemiological studies on populations exposed to radiation, which demonstrate a statistical increase of cancer risk at doses above 100 mSv. Histories of patients with highest cumulative dose and highest number of exams were further investigated by a Radiologist for appropriateness of recurrent studies and potential opportunities for reduction. Results: Out of 34762 patients, 927 (2.7%) were identified with a cumulative dose of 100 mSv and above. The highest cumulative dose (842 mSv) belonged to an oncology patient who underwent 2 diagnostic exams and 9 interventional ablative CT guided procedures. The patient with highest number of exams (56 counts) and cumulative dose of 170 mSv was a 17 year old trauma patient. An imaging history review of these two patients did not suggest any superfluous scans. Conclusion: Our limited pilot study suggests that recurrent CT exams for patients with oncologic or severe trauma history may be warranted and appropriate. As a result, for future studies we will be focusing on high dose patient cohorts not associated with oncology or severe trauma. Additionally, the review process itself has suggested areas for potential improvement in patient care, including improved documentation and Radiologist involvement in patient management. Dr. McNitt-Gray’s disclosures: Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.

60 APPLIED LIFE SCIENCES↗

TH-E-209-00: Radiation Dose Monitoring and Protocol Management

Radiation dose monitoring solutions have opened up new opportunities for medical physicists to be more involved in modern clinical radiology practices. In particular, with the help of comprehensive radiation dose data, data-driven protocol management and informed case follow up are now feasible. Significant challenges remain however and the problems faced by medical physicists are highly heterogeneous. Imaging systems from multiple vendors and a wide range of vintages co-exist in the same department and employ data communication protocols that are not fully standardized or implemented making harmonization complex. Many different solutions for radiation dose monitoring have been implemented by imaging facilities over the past few years. Such systems are based on commercial software, home-grown IT solutions, manual PACS data dumping, etc., and diverse pathways can be used to bring the data to impact clinical practice. The speakers will share their experiences with creating or tailoring radiation dose monitoring/management systems and procedures over the past few years, which vary significantly in design and scope. Topics to cover: (1) fluoroscopic dose monitoring and high radiation event handling from a large academic hospital; (2) dose monitoring and protocol optimization in pediatric radiology; and (3) development of a home-grown IT solution and dose data analysis framework. Learning Objectives: Describe the scope and range of radiation dose monitoring and protocol management in a modern radiology practice Review examples of data available from a variety of systems and how it managed and conveyed. Reflect on the role of the physicist in radiation dose awareness.

60 APPLIED LIFE SCIENCES↗

Optimization of yttrium-90 PET for simultaneous PET/MR imaging: A phantom study

Purpose: Positron emission tomography (PET) imaging of yttrium-90 in the liver post radioembolization has been shown useful for personalized dosimetry calculations and evaluation of extrahepatic deposition. The purpose of this study was to quantify the benefits of several MR-based data correction approaches offered by using a combined PET/MR system to improve Y-90 PET imaging. In particular, the feasibility of motion and partial volume corrections were investigated in a controlled phantom study. Methods: The ACR phantom was filled with an initial concentration of 8 GBq of Y-90 solution resulting in a contrast of 10:1 between the hot cylinders and the background. Y-90 PET motion correction through motion estimates from MR navigators was evaluated by using a custom-built motion stage that simulated realistic amplitudes of respiration-induced liver motion. Finally, the feasibility of an MR-based partial volume correction method was evaluated using a wavelet decomposition approach. Results: Motion resulted in a large (∼40%) loss of contrast recovery for the 8 mm cylinder in the phantom, but was corrected for after MR-based motion correction was applied. Partial volume correction improved contrast recovery by 13% for the 8 mm cylinder. Conclusions: MR-based data correction improves Y-90 PET imaging on simultaneous PET/MR systems. Assessment of these methods must be studied further in the clinical setting.

60 APPLIED LIFE SCIENCES↗

Accelerated Climate Modeling for Energy (ACME) Final Scientific/Technical Report

Seven Department of Energy (DOE) national laboratories, Universities, and Kitware, undertook a coordinated effort to build an Earth system modeling capability tailored to meet the climate change research strategic objectives of the DOE Office of Science, as well as the broader climate change application needs of other DOE programs.

97 MATHEMATICS AND COMPUTING↗

Science Breakthroughs 2030. Final report

Agriculture is a fundamental societal activity, characterized by many different landscapes, crops, markets, and participants. Food, agricultural, and biofuels products are central to the daily life of all citizens, though most do not recognize the fragility of the environment that brings forth this abundance. As is noted in the 2012 report from the President's Council of Advisors on Science and Technology, Agricultural Preparedness and the United States Agricultural Research Enterprise (PCAST, 2012) the food and agricultural system faces constant challenges in: Managing new pests, pathogens, and invasive plants. Increasing the efficiency of water use. Growing food in a changing climate. Reducing the environmental footprint of agriculture. Managing the production of bioenergy. Producing safe and nutritious food. Assisting with global food security and maintaining abundant yields. Science Breakthroughs 2030 was organized to identify the most compelling research directions in food and agriculture, in particular those empowered by the application of insights and tools from disciplines of science and engineering not typically associated with food and agricultural research. A committee appointed by the Chairman of the National Research Council explored ideas for research directions with input from the scientific community, with the objective of producing a report describing ambitious and achievable scientific pathways to address major problems and create new opportunities in food and agriculture. Following numerous meetings, a jamboree, and town hall, the appointed committee prepared a report that has subsequently become a reference for federal agencies supporting research in the food and agricultural space. It highlights five key areas for research investment with broad application across food and agriculture: integrated systems research; sensor development; data mining and information sciences, genomics; and the microbiome.

09 BIOMASS FUELS↗

Physics-Informed Deep Learning for Multiscale Water Cycle Prediction

This paper falls under Focal Area #2: Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising of a hierarchy of models (e.g., AI-driven model/component/parameterization selection).

54 ENVIRONMENTAL SCIENCES↗

A Surveillance Infrastructure for Malaria Analytics: Provisioning Data Access and Preservation of Interoperability

Background: According to the World Health Organization, malaria surveillance is weakest in countries and regions with the highest malaria burden. A core obstacle is that the data required to perform malaria surveillance are fragmented in multiple data silos distributed across geographic regions. Furthermore, consistent integrated malaria data sources are few, and a low degree of interoperability exists between them. As a result, it is difficult to identify disease trends and to plan for effective interventions. Objective: We propose the Semantics, Interoperability, and Evolution for Malaria Analytics (SIEMA) platform for use in malaria surveillance based on semantic data federation. Using this approach, it is possible to access distributed data, extend and preserve interoperability between multiple dynamic distributed malaria sources, and facilitate detection of system changes that can interrupt mission-critical global surveillance activities. Methods: We used Semantic Automated Discovery and Integration (SADI) Semantic Web Services to enable data access and improve interoperability, and the graphical user interface-enabled semantic query engine HYDRA to implement the target queries typical of malaria programs. We implemented a custom algorithm to detect changes to community-developed terminologies, data sources, and services that are core to SIEMA. This algorithm reports to a dashboard. Valet SADI is used to mitigate the impact of changes by rebuilding affected services. Results: We developed a prototype surveillance and change management platform from a combination of third-party tools, community-developed terminologies, and custom algorithms. We illustrated a methodology and core infrastructure to facilitate interoperable access to distributed data sources using SADI Semantic Web services. This degree of access makes it possible to implement complex queries needed by our user community with minimal technical skill. We implemented a dashboard that reports on terminology changes that can render the services inactive, jeopardizing system interoperability. Using this information, end users can control and reactively rebuild services to preserve interoperability and minimize service downtime. Conclusions: We introduce a framework suitable for use in malaria surveillance that supports the creation of flexible surveillance queries across distributed data resources. The platform provides interoperable access to target data sources, is domain agnostic, and with updates to core terminological resources is readily transferable to other surveillance activities. A dashboard enables users to review changes to the infrastructure and invoke system updates. The platform significantly extends the range of functionalities offered by malaria information systems, beyond the state-of-the-art.

60 APPLIED LIFE SCIENCES↗

De novo design of a homo-trimeric amantadine-binding protein

The computational design of a symmetric protein homo-oligomer that binds a symmetry-matched small molecule larger than a metal ion has not yet been achieved. We used de novo protein design to create a homo-trimeric protein that binds the C 3 symmetric small molecule drug amantadine with each protein monomer making identical interactions with each face of the small molecule. Solution NMR data show that the protein has regular three-fold symmetry and undergoes localized structural changes upon ligand binding. A high-resolution X-ray structure reveals a close overall match to the design model with the exception of water molecules in the amantadine binding site not included in the Rosetta design calculations, and a neutron structure provides experimental validation of the computationally designed hydrogen-bond networks. Exploration of approaches to generate a small molecule inducible homo-trimerization system based on the design highlight challenges that must be overcome to computationally design such systems.

59 BASIC BIOLOGICAL SCIENCES↗

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. Our ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

artificial intelligence↗

Automated Work Package: Initial Wireless Communication Platform Design, Development, and Evaluation

The Department of Energy's Light Water Reactor Sustainability Program is developing the scientific basis to ensure long-term reliability, productivity, safety, and security of the nuclear power industry in the United States. The Instrumentation, Information, and Control (II and C) pathway of the program aims to increase the role of advanced II and C technologies to achieve this objective. One of the pathway efforts at Idaho National Laboratory (INL) is to improve the work packages execution process by replacing the expensive, inefficient, bulky, complex, and error-prone paper-based work orders with automated work packages (AWPs). An AWP is an automated and dynamic presentation of the work package designed to guide the user through the work process. It is loaded on a mobile device, such as a tablet, and is capable of communicating with plant equipment and systems to acquire plant and procedure states. The AWP replaces those functions where a computer is more efficient and reliable than a human. To enable the automatic acquisition of plant data, it is necessary to design and develop a prototype platform for data exchange between the field instruments and the AWP mobile devices. The development of the platform aims to reveal issues and solutions generalizable to large-scale implementation of a similar system. Topics such as bandwidth, robustness, response time, interference, and security are usually associated with wireless communication. These concerns, along with other requirements, are listed in an earlier INL report. Specifically, the targeted issues and performance aspects in this work are relevant to the communication infrastructure from the perspective of promptness, robustness, expandability, and interoperability with different technologies. The development of a prompt system entailed significant performance optimization, including the use of parallel processing, parallel communication, modularity, noise filtering, and frequency tuning. A robust system was achieved by enforcing a persistent continuous data exchange that automatically detects and conveys a failure of any link or component in any part of the system, and that automatically restores the communication once the link or component is restored. An expandable topology was enabled by modularity and load sharing. The number of servers, mobile devices, and field instruments is not limited from a system structure point of view. The system interoperability was achieved by enforcing the independence of the field communication application from the mobile device application. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

AI-assisted detector design for the EIC (AID(2)E)

Artificial Intelligence is poised to transform the design of complex, large-scale detectors like ePIC at the future Electron Ion Collider. Featuring a central detector with additional detecting systems in the far forward and far backward regions, the ePIC experiment incorporates numerous design parameters and objectives, including performance, physics reach, and cost, constrained by mechanical and geometric limits. This project aims to develop a scalable, distributed AI-assisted detector design for the EIC (AID(2)E), employing state-of-the-art multiobjective optimization to tackle complex designs. Supported by the ePIC software stack and using G EANT 4 simulations, our approach benefits from transparent parameterization and advanced AI features. The workflow leverages the PanDA and iDDS systems, used in major experiments such as ATLAS at CERN LHC, the Rubin Observatory, and sPHENIX at RHIC, to manage the compute intensive demands of ePIC detector simulations. Tailored enhancements to the PanDA system focus on usability, scalability, automation, and monitoring. Ultimately, this project aims to establish a robust design capability, apply a distributed AI-assisted workflow to the ePIC detector, and extend its applications to the design of the second detector (Detector-2) in the EIC, as well as to calibration and alignment tasks. Additionally, we are developing advanced data science tools to efficiently navigate the complex, multidimensional trade-offs identified through this optimization process.

97 MATHEMATICS AND COMPUTING↗

Real-space observation of ergodicity transitions in artificial spin ice

Abstract Ever since its introduction by Ludwig Boltzmann, the ergodic hypothesis became a cornerstone analytical concept of equilibrium thermodynamics and complex dynamic processes. Examples of its relevance range from modeling decision-making processes in brain science to economic predictions. In condensed matter physics, ergodicity remains a concept largely investigated via theoretical and computational models. Here, we demonstrate the direct real-space observation of ergodicity transitions in a vertex-frustrated artificial spin ice. Using synchrotron-based photoemission electron microscopy we record thermally-driven moment fluctuations as a function of temperature, allowing us to directly observe transitions between ergodicity-breaking dynamics to system freezing, standing in contrast to simple trends observed for the temperature-dependent vertex populations, all while the entropy features arise as a function of temperature. These results highlight how a geometrically frustrated system, with thermodynamics strictly adhering to local ice-rule constraints, runs back-and-forth through periods of ergodicity-breaking dynamics. Ergodicity breaking and the emergence of memory is important for emergent computation, particularly in physical reservoir computing. Our work serves as further evidence of how fundamental laws of thermodynamics can be experimentally explored via real-space imaging.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Navigating the Noise: Bringing Clarity to ML Parameterization Design With O $\boldsymbol{\mathcal{O}}$(100) Ensembles

Abstract Machine‐learning (ML) parameterizations of subgrid processes (here of turbulence, convection, and radiation) may one day replace conventional parameterizations by emulating high‐resolution physics without the cost of explicit simulation. However, uncertainty about the relationship between offline and online performance (i.e., when integrated with a large‐scale general circulation model) hinders their development. Much of this uncertainty stems from limited sampling of the noisy, emergent effects of upstream ML design decisions on downstream online hybrid simulation. Our work rectifies the sampling issue via the construction of a semi‐automated, end‐to‐end pipeline for size ensembles of hybrid simulations, revealing important nuances in how systematic reductions in offline error manifest in changes to online error and online stability. For example, removing dropout and switching from a Mean Squared Error to a Mean Absolute Error loss both reduce offline error, but they have opposite effects on online error and online stability. Other design decisions, like incorporating memory, converting moisture input from specific humidity to relative humidity, using batch normalization, and training on multiple climates do not come with any such compromises. Finally, we show that ensemble sizes of may be necessary to reliably detect causally relevant differences online. By enabling rapid online experimentation at scale, we can empirically settle debates regarding subgrid ML parameterization design that would have otherwise remained unresolved in the noise.

Lin, Jerry [Department of Earth System Sciences Un↗

Examples of Use of SINBAD Database for Nuclear Data and Code Validation

Benchmark experiments can serve several purposes and the availability of suitable experimental data is fundamental to ensure that modelling tools meet the requirements of nuclear industry and licensing needs. Essentially, they are used for: - validation of nuclear cross-section data, - validation of nuclear codes and models used, - qualification and training of users through benchmarking and code comparison exercises. The Shielding Integral Benchmark Archive and Database (SINBAD) project was started in the early 1990's at the OECD Nuclear Energy Agency Data Bank (NEA DB) and the Radiation Safety Information Computational Center (RSICC) as a collection of quality experiments for validating and benchmarking computer codes and data for radiation transport and shielding applications. Currently, the SINBAD database comprises over 100 benchmark compilations and evaluations of relevance to: - reactor shielding, pressure vessel dosimetry (48); - fusion blanket neutronics (31); - accelerator shielding (23). In order to facilitate their use, the data are organized in the standardized format structure. The index and the master document (called abstract) use the Hyper Text Markup Language (HTML) format with links to text files, figures, Portable Document Format (pdf) documents and computer code inputs. The format allows easy access and forward/backward navigation among the data and has proved to be suitable, general enough and above all easy (and low-cost) to maintain. In addition to the characterization of the radiation source, description of the shielding set-up, the instrumentation and the relevant detector measurements, most sets in SINBAD contain also the deterministic or Monte Carlo radiation transport computer model used for the interpretation of the experiment and, where available, results from uncertainty analysis. The set of primary documents used for the benchmark compilation and evaluation are provided in computer readable form. The database is intended for different types of users, including nuclear data evaluators, computer code developers, experiment designers and university students. SINBAD is available from the NEA Data Bank and RSICC (see https://www.oecdnea.org/science/wprs/shielding/sinbad/). Up to now several hundreds of SINBAD packages were distributed from the NEA DB and RSICC. Since 2011 the maintenance and further development of the database is coordinated in the scope of the OECD NEA Nuclear Science Committee (NSC) Working Party on Scientific Issues of Reactor Systems (WPRS) Expert Group on Radiation Transport and Shielding (EGRTS). A key objective of the group is to identify, evaluate and preserve experimental data on shielding benchmarks. The Expert Group maintains close links with the International Reactor Physics Experiment Evaluation (IRPhE) and International Criticality Safety Benchmark Evaluation (ICSBEP) projects, as well as in co-ordination with the JEFF and EFF NEA Data Bank projects and with the SATIF community of accelerator shielding specialists. In the last years, much effort was devoted to the quality review of the available benchmark information.

42 ENGINEERING↗