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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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Artemis Lunar Surface VR/ARGOS Trainer

This proposal aims to provide insight by identifying potential risks and unknowns of lander egress and surface operations through a Mixed Reality (MR) planning, training, and analysis capability that integrates Virtual Reality (VR) simulations and the Active Response Gravity Offload System (ARGOS) in support of Artemis missions to the moon. The VR simulation will incorporate lunar digital elevation map data and imagery to provide accurate terrain of the south pole and Shackleton Crater. Date specific ephemerides will used to simulate the extreme lighting environment. Virtual representations of a lunar lander vehicle will be represented with a physical mockup of the porch and ladder assembly. Human-in-the-loop engineering test runs within ARGOS will be used to refine performance of the Mixed Reality interface with the mockup platform and define procedures for training.

Lee K Bingham↗
NASA NTRS2023

Spacesuit Fit and Mobility Assessments by Digital Human Modeling

Spacesuit Fit and Mobility Assessments by Digital Human Modeling K. Han Kim (Leidos, Inc.) Elizabeth A. Benson (KBR, Inc.) Sudhakar L. Rajulu (NASA Johnson Space Center) Spacesuits are required to accommodate safe operations for astronauts across gender and a wide variety of body shapes and sizes. This goal has been of particular importance given the increasing diversity of NASA crewmembers for upcoming Missions. While testing with design prototypes is a critical step for spacesuit development, iterative mockup design, fabrication, and human subject tests can be extremely costly and time consuming. Moreover, testing with a limited subject pool has often raised questions for validity, as test subjects need to represent the entire astronaut population, not only of the past or current, but also the future. This study is aimed at demonstrating how digital human modeling (DHM) tools have been built and directly supported NASA spacesuit developments. With DHM, the computer aided design (CAD) model of a spacesuit was integrated with human body models. Two use scenarios are presented in this paper, namely fit and mobility. For fit assessments, the suit-to-body contact and compression patterns were estimated using 3D human body scan models virtually wearing a spacesuit model. A statistical fit classifier was made from the contact patterns and applied against a large database of body scans (N=2,500). With this technique, the NASA reference design spacesuit Exploration EVA Mobility Unit (xEMU)was verified to accommodate 90% of the astronaut-like population, with the critical dimensions covering 1stto 99thpercentiles of the target body measurements. A similar technique assessed XEMU mobility. The maximum reach envelopes were considered, within which the work objects and critical hardware interfaces should be located for safe and ergonomic operations. While the reach envelope geometry varies significantly with the suit wearer’s body size and strength, the existing test data did not include the subjects critically required to define suit mobility requirements, such as very small females or large males. Using the xEMU virtual model kinematically simulated and permuted for a hypothetical wearer, however, the existing data were statistically transformed and scaled. This method enabled for a parametric estimation of the reach envelopes from the 1stpercentile female or 99thpercentile male. The outcome was successfully incorporated for requirement developments. With the new DHM tools, human integration of the spacesuit was structurally simulated and predictively assessed, which would have been otherwise impossible. Also, the needs for iterative mockup and subject tests were significantly reduced, which resulted in time and cost saving. Additional work is in progress to integrate additional vehicles, tools, and hardware with DHM framework.

K Han Kim↗
DOE OSTI2024

(Doublon) Benchmarking of Different Inverse Point Kinetics Implementations for an Autocorrected Reactimeter Algorithm

In November 2017, the Transient Reactor Test Facility returned to operation. Since that time, many transient test series have been completed, such as the Transient Heatsink Overpower Response capsule (THOR), the Transient Water Irradiation System for TREAT (TWIST), and Sirius. Each has provided valuable data for materials performance and reactor safety that can be applied in future designs. During each experimental series, detector count rates provided important information on the core behavior during transients. However, a limitation of these data is that variations in the neutron distribution during experiments can cause errors when attempting to infer reactivity evolution from detector signals. Neutron physics codes can be used to compute the flux shape variations. However, this is a poor solution when the experimental data is used for code verification, validation and uncertainty quantification. Indeed, if the output of the code is used both as a reference and to correct what the reference is compared to, the circular dependency limits the quality of the verification, validation and uncertainty quantification approach. To overcome this problem, the autocorrected reactimeter algorithm (ACRA) has been developed. This approach infers a time-dependent reactivity evolution by testing different spatial corrections and selecting the one that minimizes reactivity variations when the core is in a frozen configuration (i.e., when there is no variation in parameters affecting reactivity). However, the scope of this method was limited to transients where there were negligible thermal feedback. Indeed, the core is never in a frozen configuration when the fuel temperature varies during the whole transient. This is our motivation for developing an improved version of the ACRA that does not require frozen configurations. To develop this new algorithm, we need a precise and unbiased implementation of the inverse point kinetic equations (IPKEs) as any error in the reactivity evaluation will be propagated into the choice of the optimal spatial correction. Indeed, the previous reactimeter algorithm would use approximations, such as a negligible flux amplitude derivative, to focus on rapidity. For the numerical validation of ACRA, we aim at absolute error under for reactivity derived from signals similar to the one of this study. In this summary, we test eight different IPKE implementations. Each will process a mockup signal built for this study, similar to those that the future ACRA will process. Each reactivity output will be compared to the reference reactivity that has been used to generate the mockup signal. The implementation minimizing the difference with the reference reactivity will be used in the development of a new ACRA formulation.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Experiences with a Flexible User Research Process to Build Data Change Tools

Scientific software development processes are understood to be distinct from commercial software development practices due to uncertain and evolving states of scientific knowledge. Sustaining these software products is a recognized challenge, but under-examined is the usability and usefulness of such tools to their scientific end users. User research is a well-established set of techniques (e.g., interviews, mockups, usability tests) applied in commercial software projects to develop foundational, generative, and evaluative insights about products and the people who use them. Currently these approaches are not commonly applied and discussed in scientific software development work. The use of user research techniques in scientific environments can be challenging due to the nascent, fluid problem spaces of scientific work, varying scope of projects and their user communities, and funding/economic constraints on projects.In this paper, we reflect on our experiences undertaking a multi-method user research process in the Deduce project. The Deduce project is investigating data change to develop metrics, methods, and tools that will help scientists make decisions around data change. There is a lack of common terminology since the concept of systematically measuring and managing data change is under explored in scientific environments. To bridge this gap we conducted user research that focuses on user practices, needs, and motivations to help us design and develop metrics and tools for data change. This paper contributes reflections and the lessons we have learned from our experiences. We offer key takeaways for scientific software project teams to effectively and flexibly incorporate similar processes into their projects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Development of the Underwater Disc Saw Used to Segment the Internals of Taiwan Research Reactor - 20038

Taiwan Research Reactor will be dismantled in the period of 2022 to 2027 according to the approved dismantling plan. Based on the sampling and analyzing results, some internals of Taiwan Research Reactor must be segmented under the water because of their higher radiation, and the calandria is one of them. To dismantle this calandria, Institute of Nuclear Energy Research develops an underwater disc saw that is driven by a hydraulic pump and will be used to segment the shell of the calandria. In this article, Taiwan Research Reactor and the structure of the calandria are briefly depicted, and the segmentation processes of this calandria and the design of this disc saw are also included. Besides, the trial of cutting the shell of the simplified full size calandria mockup is briefly demonstrated in this article. Further tests will be performed in the near future to figure out which parts or functions of this disc saw need to be modified to get better cutting performance. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Inspection Tools for Hanford Tanks and Waste Transport Systems - 20444

Recent integrity issues in the double-shell tanks (DST) at Hanford have motivated the need for developing innovative tools that can provide information regarding the health of the tanks. These issues include the primary linear failure of AY-102 and recent concerns of thinning in the DST secondary liners. Other concerns include erosion or corrosion on transfer lines and processing pipes. In recent years, Florida International University (FIU) has supported DOE-EM by developing tools that can assist in understanding the health of tanks and waste transport system at Hanford. More specifically, FIU has developed a miniature rover that can be deployed through small risers and gain access to refractory slots in the Hanford DSTs. It traverses through the slots on the primary liner upside down via magnets to avoid debris in the slots. Recent modifications include a spring loaded magnetic arm that allows the unit to traverse over large weld seams but does not reduce the overall functionality of the system. The system has also incorporated a control capsule that will sit within the annulus of the tank and improves on issues related to signal and voltage loss over long tether lines. Lastly, the unit is also being augmented with a second module that will include a means to prep the tank surface and obtain a thickness measurement using a dual element ultrasonic sensor. FIU has also developed a 6-inch peristaltic pipe crawler that operates similar to the previous pipe crawlers developed at FIU. This crawler is a marsupial type crawler that will navigate through the 6-inch drain lines, and deploy a small rover at the entrance of the drain slots. This rover will also traverse upside down on the secondary liner and provide information regarding the health of the liner. An initial prototype for the crawler unit has been developed, assembled and tested. The system is pneumatic and consists of three modules - two grippers and one extender. The validation tests are conducted in a mockup of the drain lines and demonstrate the system's ability to navigate through long pipe lengths and elbows. In this paper, a general overview of each of the aforementioned systems is presented along with results from testing and demonstrations that shows the applicability of each system. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Artificial Intelligence Application to D and D - 20492

As aging facilities across the DOE complex await decommissioning, there is an ongoing need to understand any changes in the structural conditions. Many of these facilities were built over 50 years ago and, in some cases, these facilities have gone beyond the expected operational lifetime. Many facilities have been placed in a state of 'cold and dark,' sitting unused and awaiting decommissioning. Especially challenging are the aging facilities that provide unique operational/production capabilities to support critical DOE missions and cannot be shut down. In any of these scenarios, the structural integrity of these facilities may become compromised as time passes. It is critical that adequate inspections be performed on a continual basis and that the data collected undergoes sufficient analysis to support timely identification of any new or worsening structural issues as well as prompt needed maintenance and repairs to maintain the facilities in a safe condition. In recent days, Artificial Intelligence (AI) [1] and its application to various domains are growing at fast speed. FIU is performing research in this area and exploring the associated technologies to solve nuclear decommissioning problems. Artificial intelligence refers to the capability of a program to autonomously act, react and adapt to the working environment. AI enables the machine to behave like humans and perform the cognitive functions such as 'learning' and 'problem solving'. AI systems gradually moving from traditional approaches (algorithms and expert systems) towards more efficient and advanced technologies (machine learning [1] and deep learning [2] [3]). AI is the study of algorithms and statistical models that is being used by computers to perform specific tasks without using explicit instructions. FIU is working to develop a pilot-scale infrastructure to implement structural health monitoring using AI technologies with focus on machine learning, deep learning. This research is focused on Computer Vision/Image Classification area of AI applications. This can also be expanded to other areas of AI related to Object Recognition and Character Recognition in images. In addition to utilizing existing data sets, FIU will collect and investigate image and video data using FIU test-bed mockups to monitor structural health of the facility. Resulting data will be processed and analyzed using machine learning/deep learning technologies. The proposed pilot system is intended to serve as a starting point to engage the DOE field sites on related data sets and their decision making needs. It is anticipated that proposed machine learning/deep learning technologies can be effectively employed using anomaly detection to solve EM challenges in surveillance and maintenance of the D and D facilities. FIU will work with research stakeholders to identify applications at various sites and other DOE facilities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

A digital twin platform for building performance monitoring and optimization: Performance simulation and case studies

Advancements in sensor technology, data analytics, affordable compute, and communication infrastructure have paved the way for Digital Twin technology in optimizing building operations and controls. This study presents the development of an open and interoperable web-based Digital Twin platform for integrating diverse data streams and facilitating effective user interactions. The platform utilizes modern technologies for the web framework and time-series data management, ensuring scalability and responsiveness. The backend supports seamless integration of diverse data sources and emulators, incorporating data from building sensors and meters, external weather Application Programming Interfaces, and advanced EnergyPlus simulation models of the building and its energy systems including the Distributed Energy Resources that are formulated in Functional Mockup Units. A simulation case study was conducted with FlexLab, a test facility on Lawrence Berkeley National Laboratory campus. The case study includes normal operations, Distributed Energy Resource integration, and power outage scenarios, to illustrate the Digital Twin’s ability to provide critical insights into energy performance and thermal resilience. The results demonstrated the platform’s potential as a decision-support tool for optimizing building energy performance and enhancing resilience against extreme weather events. Future work will focus on deploying the Digital Twin platform to a real building for field validation, extending its capabilities to cover more scenarios such as bidirectional Electric Vehicle interactions, and enhancing user engagement.

EnergyPlus↗
DOE OSTI2021

Analysis of ZPPR-15 experimental data for VTR software validation

As part of the Versatile Test Reactor (VTR) program, extensive validation work is being performed to demonstrate the fidelity of the Argonne Reactor Code (ARC) software package presently used for the core design studies. It is anticipated that this software will be also used for initial operations although additional software may be introduced at a later time to supplement or replace some components. The validation work was focused on accumulating reactor models that are consistent with the VTR and thus can be used to validate the accuracy of predictions made by the software used to design and operate the VTR. The U.S. does not have any active experimental facilities that can neutronically mockup the VTR core design. However, in the past, the U.S. had extensive experimental facilities for fast reactor neutronics. In that regard, the ZPPR-15 experiments carried out at ANL during the 1980s work best because the fuel form is closest to the VTR design, there is a considerable amount of processed data available for use, and existing staff are already familiar with the experimental machine and measurements. Because of previous collaborative work, many of the ZPPR-15 loadings of interest have already been processed into MCNP and preliminary ARC models, and a full uncertainty quantification has already been completed for many of the ZPPR-15 measurements. This manuscript covers the recent analysis work on the ZPPR-15 experiments and compares it with the experimental results. With respect to the ARC software components, this manuscript focuses on validation of the MC 2 , DIF3D and GAMSOR using the ZPPR-15 experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Direct, efficient and selective capture of low concentration of CO 2 from natural gas flue gas using a high temperature tubular carbon capture membrane

Natural gas (NG) fired power plants emit low concentration (4–5%) of CO 2 , which presents additional technical and economic challenges to the current benchmark amine absorption technology. The newly emerged high-temperature multiphase membranes operated on molten carbonate (MC) chemistry for CO 2 capture/separation/conversion have been demonstrated with great potential to meet this challenge. In this study, we report on the CO 2 capture performance of such a membrane in tubular geometry from a mockup NG flue gas. The membrane is comprised of a mixture of Gd 0.20 Ce 0.80 O 1.95 (GDC) and MC, in which GDC forms a porous skeleton to contain MC. Here, we show that the membrane with a dimension of 6.1 mm in outer diameter, 5.1 mm in inner diameter and 5 cm in effective length (resulting in 4cm 2 effective surface area) can achieve a CO 2 flux density of 0.46–0.55 mL/min·cm 2 at 650°C, capturing 97% pure CO 2 at a rate of 37–42% from 5%CO 2 –N 2 using moistened Ar as the sweep gas. The level of performance demonstrated by this study suites the membrane well for stationary CO 2 capture from NG power plants.

03 NATURAL GAS↗
DOE OSTI2021

Quantitative imaging and automated fuel pin identification for passive gamma emission tomography

Compliance of member States to the Treaty on the Non-Proliferation of Nuclear Weapons is monitored through nuclear safeguards. The Passive Gamma Emission Tomography (PGET) system is a novel instrument developed within the framework of the International Atomic Energy Agency (IAEA) project JNT 1510, which included the European Commission, Finland, Hungary and Sweden. The PGET is used for the verification of spent nuclear fuel stored in water pools. Advanced image reconstruction techniques are crucial for obtaining high-quality cross-sectional images of the spent-fuel bundle to allow inspectors of the IAEA to monitor nuclear material and promptly identify its diversion. In this work, we have developed a software suite to accurately reconstruct the spent-fuel cross sectional image, automatically identify present fuel rods, and estimate their activity. Unique image reconstruction challenges are posed by the measurement of spent fuel, due to its high activity and the self-attenuation. While the former is mitigated by detector physical collimation, we implemented a linear forward model to model the detector responses to the fuel rods inside the PGET, to account for the latter. The image reconstruction is performed by solving a regularized linear inverse problem using the fast-iterative shrinkage-thresholding algorithm. We have also implemented the traditional filtered back projection (FBP) method based on the inverse Radon transform for comparison and applied both methods to reconstruct images of simulated mockup fuel assemblies. Higher image resolution and fewer reconstruction artifacts were obtained with the inverse-problem approach, with the mean-square-error reduced by 50%, and the structural-similarity improved by 200%. We then used a convolutional neural network (CNN) to automatically identify the bundle type and extract the pin locations from the images; the estimated activity levels finally being compared with the ground truth. The proposed computational methods accurately estimated the activity levels of the present pins, with an associated uncertainty of approximately 5%.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A Q-band frequency tunable Doppler backscattering (DBS) system for pedestal and scrape-off layer density fluctuation and flow measurements in the DIII-D tokamak

We present the design and laboratory tests for a new Q-band frequency tunable Doppler backscattering (DBS) system suitable for probing poloidal wavenumber kñ = 6–8 cm−1 density fluctuations and their flow velocities in the pedestal and scape-off layer (SOL) of the DIII-D tokamak. This system will provide new measurements in the increasingly important and under-diagnosed far pedestal and SOL plasma regions. These results are important for experimental transport studies and necessary for the validation of transport models, both of which are important to fusion energy research. The use of a single tunable frequency reduces the complexity and potential failure points as compared to a multichannel system. This new system utilizes a 33–50 GHz tunable source and will be integrated into the current V-band DBS in DIII-D using a broadband Q- and V-band multiplexer. A full-scale mockup of the quasi-optical system was used to test and optimize the performance. These tests include beam profile measurements at different distances (and angles) from a paraboloidal focusing and steering mirror. The measurements cover the full frequency range 33–75 GHz of the integrated/combined Q–V band DBS system and target a large radial coverage of the low-field side of the plasma from ρ = 1.1 to ρ = 0.5, where ρ is the normalized flux surface radial coordinate.

Instruments & Instrumentation↗
DOE OSTI2023

Ceci N’est Pas Une Bombe: Lessons from a Field Experiment Using Neutron and Gamma Measurements to Confirm the Absence of Nuclear Weapons

In March 2023, the UN Institute for Disarmament Research held a verification experiment that included a mockup onsite inspection at a former military facility in the municipality of Menzingen, Switzerland. The experiment included a visit to the site by an inspection team, accompanied by the host team. Among other activities, radiation measurements were used to confirm the non-nuclear nature of selected items stored onsite. In this paper, we discuss the neutron and gamma measurement systems used during the experiment and the inspection protocols followed to confirm the absence of nuclear weapons. Furthermore, results from the experiment and a laboratory reproduction are presented, before concluding with lessons learned for how absence-confirmation measurements can help support verification of future arms control agreements.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

Nb 3 Sn coating of SRF cavity by cosputtering from a composite target

Here, we deposited an Nb 3 Sn film on the inner surface of a 2.6 GHz Nb superconducting radio frequency cavity by cosputtering using a composite of Nb and Sn tube targets in a DC cylindrical magnetron sputtering system, followed by the thermal annealing of the coated cavity. An aluminum mockup cavity, replicating a 2.6 GHz Nb SRF cavity geometry, was utilized to optimize deposition parameters, resulting in cosputtered Nb–Sn films with an Sn content of 32–42 at. % on the beam tubes and equator positions. Several annealing conditions were investigated to improve the surface homogeneity of the Nb 3 Sn film. The best cosputtered Nb–Sn film was achieved after annealing at 600 °C for 6 h, followed by annealing at 950 °C for 1 h. The best process was applied to a Nb cavity, which was RF tested in a cryogenic dewar. RF testing of the Nb 3 Sn-coated cavity demonstrated a superconducting transition temperature of 17.78 K. The Nb 3 Sn cavity underwent light Sn recoating, followed by additional RF testing, resulting in the enhancement of the RF performance, primarily due to the improved surface homogeneity of the Nb 3 Sn coating.

Nb3Sn film↗
DOE OSTI2020

BEEAM (Building Electrical Efficiency Analysis Model) [SWR-20-107]

Modern high-performance buildings exhibit an increasing number of building loads that use direct current (DC) electricity internally, rather than alternating current (AC), due to the advent of low-cost computing and advanced power electronics. Powering DC devices from the AC grid requires AC/DC power conversion, which introduces energy losses and reduces efficiency. As DC loads proliferate, the cumulative wasted energy associated with hundreds of millions of AC/DC converters has become one of the broadest energy savings opportunities in buildings. DC power distribution systems have been proposed as an elegant and transformative solution to the problem of DC devices. In a DC distribution system, the building's wires carry DC electricity, rather than AC; and a few centralized, highly efficient AC/DC converters replace the many smaller, less efficient converters that serve individual DC loads. Unfortunately, the trade-offs associated with DC distribution systems are not well understood. Reported energy savings associated with DC power distribution differ widely and have not been well validated. The Building Electrical Efficiency Analysis Model (BEEAM) is a Modelica library that simulates the efficiency of building electrical distribution systems using harmonic power flow. BEEAM can model a wide variety of building distribution topologies, including three-phase AC, single-phase AC, unipolar DC, bipolar DC, and hybrid networks under both balanced and unbalanced load conditions. BEEAM accurately models power electronic converter losses, provides granular estimates of losses throughout the distribution system, and properly models efficiency at part load conditions. Users can package BEEAM within a functional mockup unit (FMU), enabling co-simulation with other modeling platform, such as EnergyPlus. In summary, BEEAM provides a tool suite for fair and accurate comparison of the efficiency of building electrical distribution systems, including AC, DC, and hybrid systems.

Frank, Stephen↗
DOE OSTI2020

Full-Scale Assembly 30 cm Drop Test

Can Spent Nuclear Fuel withstand the shocks and vibrations experienced during normal conditions of transport? This question was the motivation for the multi-modal transportation test (MMTT) (Summer 2017), 1/3-scale cask 30 cm drop test (December 2018), and full-scale assembly 30 cm drop tests (June 2019). The full-scale ENSA ENUN 32P cask with 3 surrogate 17x17 PWR assemblies was used in the MMTT. The 1/3-scale cask was a mockup of this cask. The 30 cm drop tests provided the accelerations on the 1/3-scale dummy assemblies. These data were used to design full-scale assembly drop tests with the goal to quantify the strain fuel rods experience inside a cask when dropped from a height of 30 cm. The drop tests were first done with the dummy and then with the surrogate assembly. This paper presents the preliminary results of the tests.

Transportation↗
DOE OSTI2024

Progress in the design of the future circular collider FCC-ee interaction region

In this paper we discuss the latest developments for the FCC-ee interaction region layout, which represents one of the key ingredients to establish the feasibility of the FCC-ee. The collider has to achieve extremely high luminosities over a wide range of center-of-mass energies with two or four interaction points. The complex final focus hosted in the detector region has to be carefully designed, and the impact of beam losses and of any type of synchrotron radiation generated in the interaction region, including beamstrahlung, have to be evaluated in detail with simulations. We give an overview of the progress of the whole machine-detector-interface-related studies, among which are the updated mechanical model of the interaction region, the plans for a novel R&D activity of a IR mockup which is just starting, the collimation scheme and evaluation of beam induced backgrounds in the detectors, evaluation of radiation dose in the experimental area, and MDI integration with the detector.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Design and Analysis of a Halo-Measurement Diagnostics

A large dynamical-range diagnostics (LDRD) design at Jefferson Lab will be used at the FAST-IOTA injector to measure the transverse distribution of halo associated with a high-charge electron beam. One important aspect of this work is to explore the halo distribution when the beam has significant angular momentum (i.e. is magnetized). The beam distribution is measured by recording radiation produced as the beam impinges a YAG:Ce screen. The optical radiation is split with a fraction directed to a charged-couple device (CCD) camera. The other part of the radiation is reflected by a digital micromirror device (DMD) that masks the core of the beam distribution. Combining the images recorded by the two cameras provides a measurement of the transverse distribution with over a large dynamical range. The design and analysis of the optical system will be discussed including optical simulation using SRW and the result of a mockup experiment to test the performances of the system will be presented.

43 PARTICLE ACCELERATORS↗