Project ATS-A
Communications, meteorological, and scientific experiments for applications technology satellite having passive gradient control system
METEOROLOGICAL PROBE↗
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Projecting Permafrost Thaw of Sub-Arctic Tundra With a Thermodynamic Model Calibrated to Site Measurements
Northern circumpolar permafrost thaw affects global carbon cycling, as large amounts of stored soil carbon becomes accessible to microbial breakdown under a warming climate. The magnitude of carbon release is linked to the extent of permafrost thaw, which is locally variable and controlled by soil thermodynamics. Soil thermodynamic properties, such as thermal diffusivity, govern the reactivity of the soil-atmosphere thermal gradient, and are controlled by soil composition and drainage. In order to project permafrost thaw for an Alaskan tundra experimental site, we used seven years of site data to calibrate a soil thermodynamic model using a data assimilation technique. The model reproduced seasonal and interannual temperature dynamics for shallow (5–40 cm) and deep soil layers (2–4 m), and simulations of seasonal thaw depth closely matched observed data. The model was then used to project permafrost thaw at the site to the year 2100 using climate forcing data for three future climate scenarios (RCP 4.5, 6.0, and 8.5). Minimal permafrost thawing occurred until mean annual air temperatures rose above the freezing point, after which we measured over a 1 m increase in thaw depth for every 1 °C rise in mean annual air temperature. Under no projected warming scenario was permafrost remaining in the upper 3 m of soil by 2100. We demonstrated an effective data assimilation method that optimizes parameterization of a soil thermodynamic model. The sensitivity of local permafrost to climate warming illustrates the vulnerability of sub-Arctic tundra ecosystems to significant and rapid soil thawing.
54 ENVIRONMENTAL SCIENCES↗
The future of the El Niño–Southern Oscillation: using large ensembles to illuminate time-varying responses and inter-model differences
Future changes in the El Niño–Southern Oscillation (ENSO) are uncertain, both because future projections differ between climate models and because the large internal variability of ENSO clouds the diagnosis of forced changes in observations and individual climate model simulations. By leveraging 14 single model initial-condition large ensembles (SMILEs), we robustly isolate the time-evolving response of ENSO sea surface temperature (SST) variability to anthropogenic forcing from internal variability in each SMILE. We find nonlinear changes in time in many models and considerable inter-model differences in projected changes in ENSO and the mean-state tropical Pacific zonal SST gradient. We demonstrate a linear relationship between the change in ENSO SST variability and the tropical Pacific zonal SST gradient, although forced changes in the tropical Pacific SST gradient often occur later in the 21st century than changes in ENSO SST variability, which can lead to departures from the linear relationship. Single-forcing SMILEs show a potential contribution of anthropogenic forcing (aerosols and greenhouse gases) to historical changes in ENSO SST variability, while the observed historical strengthening of the tropical Pacific SST gradient sits on the edge of the model spread for those models for which single-forcing SMILEs are available. Our results highlight the value of SMILEs for investigating time-dependent forced responses and inter-model differences in ENSO projections. The nonlinear changes in ENSO SST variability found in many models demonstrate the importance of characterizing this time-dependent behavior, as it implies that ENSO impacts may vary dramatically throughout the 21st century.
54 ENVIRONMENTAL SCIENCES↗
Computational diagnostics for flame acceleration and transition to detonation in a hydrogen/air mixture
A new computational diagnostic method for pressure-induced compressibility is proposed by projecting its local contribution to the chemical explosive mode (CEM) in the chemical explosive mode analysis (CEMA) framework. The new method is validated for the study of detonation development during the deflagration-to-detonation transition (DDT) process. The flame characteristics are identified through the quantification of individual CEM contributions of chemical reaction, diffusion, and pressure-induced compressibility. Numerical simulations are performed to investigate the DDT processes in a stoichiometric hydrogen-air mixture. A Godunov algorithm, fifth-order in space, and third-order in time are used to solve the fully compressible Navier-Stokes equations on a dynamically adapting mesh. A single-step, calibrated chemical diffusive model (CDM) described by Arrhenius kinetics is used for energy release and conservation between the fuel and the product. The new diagnostic method is first applied to onedimensional (1D) canonical flame configurations followed by two-dimensional (2D) simulations of DDT in an obstructed channel where different detonation initiation scenarios are examined using the new CEMA projection formulation. Detailed examinations of the idealized configuration of detonation initiation through shock focusing mechanism at a flame front are also studied using the new formulation. A comparison of the currently proposed CEMA projection and the original formulation by the authors suggests that including the pressure-induced compressibility is essential for the use of CEMA in DDT process. The results also show that the new formulation of CEMA projection can successively capture the detonation initiation through either a gradient mechanism or a direct initiation mechanism, and therefore can be used as an effective local analytical tool for the computational diagnostics of detonation initiation in a DDT process. It was found that detonation development is characterized by a strong contribution of chemistry role to the CEM which is pivotal to the initiation of detonation. The role of compressibility is found enhanced at the edge of the detonation front where diffusion was found to have minimal effects on detonation development.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A Monte Carlo model for 3D grain evolution during welding
Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bezier curves, which allow for the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. Furthermore, the model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.
36 MATERIALS SCIENCE↗
WE-AB-BRA-12: Virtual Endoscope Tracking for Endoscopy-CT Image Registration
Purpose: The use of endoscopy in radiotherapy will remain limited until we can register endoscopic video to CT using standard clinical equipment. In this phantom study we tested a registration method using virtual endoscopy to measure CT-space positions from endoscopic video. Methods: Our phantom is a contorted clay cylinder with 2-mm-diameter markers in the luminal surface. These markers are visible on both CT and endoscopic video. Virtual endoscope images were rendered from a polygonal mesh created by segmenting the phantom’s luminal surface on CT. We tested registration accuracy by tracking the endoscope’s 6-degree-of-freedom coordinates frame-to-frame in a video recorded as it moved through the phantom, and using these coordinates to measure CT-space positions of markers visible in the final frame. To track the endoscope we used the Nelder-Mead method to search for coordinates that render the virtual frame most similar to the next recorded frame. We measured the endoscope’s initial-frame coordinates using a set of visible markers, and for image similarity we used a combination of mutual information and gradient alignment. CT-space marker positions were measured by projecting their final-frame pixel addresses through the virtual endoscope to intersect with the mesh. Registration error was quantified as the distance between this intersection and the marker’s manually-selected CT-space position. Results: Tracking succeeded for 6 of 8 videos, for which the mean registration error was 4.8±3.5mm (24 measurements total). The mean error in the axial direction (3.1±3.3mm) was larger than in the sagittal or coronal directions (2.0±2.3mm, 1.7±1.6mm). In the other 2 videos, the virtual endoscope got stuck in a false minimum. Conclusion: Our method can successfully track the position and orientation of an endoscope, and it provides accurate spatial mapping from endoscopic video to CT. This method will serve as a foundation for an endoscopy-CT registration framework that is clinically valuable and requires no specialized equipment.
60 APPLIED LIFE SCIENCES↗
Impact of CO 2 on the Evolution of Microbial Communities Exposed to Carbon Storage Conditions, Enhanced Oil Recovery, and CO 2 Leakage
Geologic carbon storage (GCS) is a crucial part of a proposed mitigation strategy to reduce the anthropogenic carbon dioxide (CO 2 ) emissions to the atmosphere. During this process, CO 2 is injected as super critical carbon dioxide (SC-CO 2 ) in confined deep subsurface storage units, such as saline aquifers and depleted oil reservoirs. The deposition of vast amounts of CO 2 in subsurface geologic formations could unintentionally lead to CO 2 leakage into overlying freshwater aquifers. Introduction of CO 2 into these subsurface environments will greatly increase the CO 2 concentration and will create CO 2 concentration gradients that drive changes in the microbial communities present. While it is expected that altered microbial communities will impact the biogeochemistry of the subsurface, there is no information available on how CO 2 gradients will impact these communities. The overarching goal of this project is to understand how CO 2 exposure will impact subsurface microbial communities at temperatures and pressures that are relevant to GCS and CO 2 leakage scenarios. To meet this goal, unfiltered, aqueous samples from a deep saline aquifer, a depleted oil reservoir, and a fresh water aquifer were exposed to varied concentrations of CO 2 at reservoir pressure and temperature. The microbial ecology of the samples was examined using molecular, DNA-based techniques. The results from these studies were also compared across the sites to determine any existing trends. Results reveal that increasing CO 2 leads to decreased DNA concentrations regardless of the site, suggesting that microbial processes will be significantly hindered or absent nearest the CO 2 injection/leakage plume where CO 2 concentrations are highest. At CO 2 exposures expected downgradient from the CO 2 plume, selected microorganisms emerged as dominant in the CO 2 exposed conditions. Results suggest that the altered microbial community was site specific and highly dependent on pH. The site-dependent results suggest a limited ability to predict the emerging dominant species for other CO 2 -exposed environments. This study improves the understanding of how a subsurface microbial community may respond to conditions expected from GCS and CO 2 leakage. This is the first step for understanding how a CO 2 -altered microbial community may impact injectivity, permanence of stored CO 2 , and subsurface water quality. Future work with microbial communities from new subsurface sites would increase the current understanding of this project. Additionally, incorporation of metagenomic methods would increase understanding of potential microbial processes that may be prevalent in CO 2 exposed environments.
54 ENVIRONMENTAL SCIENCES↗
Impact of CO 2 on the Evolution of Microbial Communities Exposed to Carbon Storage Conditions, Enhanced Oil Recovery, and CO 2 Leakage
Geologic carbon storage (GCS) is a crucial part of a proposed mitigation strategy to reduce the anthropogenic carbon dioxide (CO 2 ) emissions to the atmosphere. During this process, CO 2 is injected as super critical carbon dioxide (SC-CO 2 ) in confined deep subsurface storage units, such as saline aquifers and depleted oil reservoirs. The deposition of vast amounts of CO 2 in subsurface geologic formations could unintentionally lead to CO 2 leakage into overlying freshwater aquifers. Introduction of CO 2 into these subsurface environments will greatly increase the CO 2 2 concentration and will create CO 2 concentration gradients that drive changes in the microbial communities present. While it is expected that altered microbial communities will impact the biogeochemistry of the subsurface, there is no information available on how CO 2 gradients will impact these communities. The overarching goal of this project is to understand how CO 2 exposure will impact subsurface microbial communities at temperatures and pressures that are relevant to GCS and CO 2 leakage scenarios. To meet this goal, unfiltered, aqueous samples from a deep saline aquifer, a depleted oil reservoir, and a fresh water aquifer were exposed to varied concentrations of CO 2 at reservoir pressure and temperature. The microbial ecology of the samples was examined using molecular, DNA-based techniques. The results from these studies were also compared across the sites to determine any existing trends. Results reveal that increasing CO 2 leads to decreased DNA concentrations regardless of the site, suggesting that microbial processes will be significantly hindered or absent nearest the CO 2 injection/leakage plume where CO 2 concentrations are highest. At CO 2 exposures expected downgradient from the CO 2 plume, selected microorganisms emerged as dominant in the CO 2 exposed conditions. Results suggest that the altered microbial community was site specific and highly dependent on pH. The site-dependent results suggest a limited ability to predict the emerging dominant species for other CO 2 exposed environments. This study improves the understanding of how a subsurface microbial community may respond to conditions expected from GCS and CO 2 leakage. This is the first step for understanding how a CO 2 -altered microbial community may impact injectivity, permanence of stored CO 2 , and subsurface water quality. Future work with microbial communities from new subsurface sites would increase the current understanding of this project. Additionally, incorporation of metagenomic methods would increase understanding of potential microbial processes that may be prevalent in CO 2 exposed environments.
54 ENVIRONMENTAL SCIENCES↗
Reevaluating linear accelerator shielding for 320 µA of proton beam
The collider-accelerator facilities at Brookhaven National Laboratory (BNL) have been developing since the completion of the experiments they were originally built for, and their uses for research have evolved over the years with a variety of users. With these changes, we must be careful to avoid potential radiation hazards of worst-case scenarios, although these faults are unlikely. One of these changes in the Collider-Accelerator Department (C-AD) is the replacement of power supplies and upgrading the linear accelerator (Linac) radiofrequency system to allow the Brookhaven Linac Isotope Producer (BLIP) to use a 320 μA average current. This current of 320 μA is greater than any current that the Linac shielding has withstood before, and thus this project in reevaluating the Linac shielding is necessary to ensure all future Linac research is conducted safely. Particularly, this project aims to estimate the radiation doses in the Alternating Gradient Synchrotron (AGS) tunnel near the Linac tunnel and in the equipment bay room near the gate valve of the last tank (tank 9) of Linac. To do this, we used the particle transport code, Monte Carlo N-Particle 6.2 (MCNP6.2), to perform the simulation and model the facilities of Linac and AGS at BNL. This simulation allowed us to investigate the extent of radiation dose rates in various areas of the facilities by placing detectors in specific locations. We could therefore determine whether the dose rates due to these faults is acceptable for limits set by the Department of Energy (DOE) and BNL, and if the shielding is sufficient.
43 PARTICLE ACCELERATORS↗
Advanced Data Science Model for Detecting Intelligent Malware
This study focused on developing a robust artificial intelligence (AI) model capable of detecting and characterizing advanced malware in Internet of Things (IoT) devices using network data. By analyzing network traffic with various machine learning (ML) models, our AI model can identify and characterize malicious activities to significantly improve malware detection accuracy and reliability as compared to traditional methods. The developed AI/ML model was trained using network data from IoT devices, leveraging classifiers such as Random Forest, Gradient Boosting, AdaBoost, and others to optimize detection performance. This project demonstrates a scalable framework for real-time malware detection and characterization in IoT networks, capable of identifying infected devices and facilitating the necessary steps to remove or isolate them, thereby preventing further infections. Although digital twin (DT) integration is not yet implemented in the current model, it represents a promising future enhancement. By creating a virtual replica of physical IoT devices, DT technology would allow for real-time monitoring and analysis without directly accessing operational technology, thus reducing the risk of compromising or reducing the performance of actual devices. This integration would further enhance the security of IoT ecosystems, combining AI technology to better flag and detect indications of malware-infected devices within a nuclear system environment.
42 ENGINEERING↗
Differential surface models for tactile perception of shape and on-line tracking of features
Tactile perception of shape involves an on-line controller and a shape perceptor. The purpose of the on-line controller is to maintain gliding or rolling contact with the surface, and collect information, or track specific features of the surface such as edges of a certain sharpness. The shape perceptor uses the information to perceive, estimate the parameters of, or recognize the shape. The differential surface model depends on the information collected and on the a priori information known about the robot and its physical parameters. These differential models are certain functionals that are projections of the dynamics of the robot onto the surface gradient or onto the tangent plane. A number of differential properties may be directly measured from present day tactile sensors. Others may have to be indirectly computed from measurements. Others may constitute design objectives for distributed tactile sensors of the future. A parameterization of the surface leads to linear and nonlinear sequential parameter estimation techniques for identification of the surface. Many interesting compromises between measurement and computation are possible.
Hemami, H.↗
Modeling Creep Effects in Advanced SiC/SiC Composites
Because advanced SiC/SiC composites are projected to be used for aerospace components with large thermal gradients at high temperatures, efforts are on-going at NASA Glenn to develop approaches for modeling the anticipated creep behavior of these materials and its subsequent effects on such key composite properties as internal residual stress, proportional limit stress, ultimate tensile strength, and rupture life. Based primarily on in-plane creep data for 2D panels, this presentation describes initial modeling progress at applied composite stresses below matrix cracking for some high performance SiC/SiC composite systems recently developed at NASA. Studies are described to develop creep and rupture models using empirical, mechanical analog, and mechanistic approaches, and to implement them into finite element codes for improved component design and life modeling
Lang, Jerry↗
Is the 80 - 20 Principle a Friend or a Foe? Critical Remarks on the Dominant Flat Gradient - 17206
The well-known 80 - 20 principle, also known as the Pareto principle, describes the fact that usually 80 % of the result is achieved by 20 % of the effort, because many probability distributions are caused by a power-law. This principle is valued in the realm of project management and management in general because of the fast progress which generally takes place in the first fifth of the process. If the final result is not exactly specified or resources are spent wisely, 100 % of the planned result will be reached easily. However, in nuclear business safety is a principal parameter. Therefore precision is inevitable. In long-lasting projects the bad end of the Pareto-distribution is dominant: The very shallowly-inclined gradient at the end of the graph means that results at that point come at a very high effort and cost. The graph reaches the 100% only asymptomatically, meaning the initially projected results are never met. Especially if in earlier project phases the Pareto principle is applied very successfully, a lot of work is transferred to the future. For example, in decommissioning projects the waste often is badly characterized causing an enormous effort in the process of characterization and qualification. Especially if funding or time are limited, it is important to be aware of the asymmetric distribution of applied work and result. The 80 - 20 principle is a great advantage, if you start a project and respect the asymmetric distribution of applied resources and results in your project plan. Especially in long-lasting projects with changing perspectives, this asymmetric distribution may cause massive delays and expansion of costs, because small changes near the end cause large/big effort due to consequences on the existing data. If the proper goal of a project is not entirely known in the beginning, it is very probable that the last 5 - 10 % of the result will cause major financial threat and extensions of the estimated time frame. If funding or time are limited, it is almost impossible to readjust a project in the estimated frame of resources. In this case a complete restart of the project may be more reasonable than a long-lasting change management with uncertain results. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Reduced El NiñO Variability in the Mid-Pliocene According to the Pliomip2 Ensemble
The mid-Pliocene warm period (3.264–3.025 Ma) is the most recent geological period during which atmospheric CO 2 levels were similar to recent historical values (∼400 ppm). Several proxy reconstructions for the mid-Pliocene show highly reduced zonal sea surface temperature (SST) gradients in the tropical Pacific Ocean, indicating an El Niño-like mean state. However, past modelling studies do not show these highly reduced gradients. Efforts to understand mid-Pliocene climate dynamics have led to the Pliocene Model Intercomparison Project (PlioMIP). Results from the first phase (PlioMIP1) showed clear El Niño variability (albeit significantly reduced) and did not show the greatly reduced time-mean zonal SST gradient suggested by some of the proxies. In this work, we study El Niño–Southern Oscillation (ENSO) variability in the PlioMIP2 ensemble, which consists of additional global coupled climate models and updated boundary conditions compared to PlioMIP1. We quantify ENSO amplitude, period, spatial structure and “flavour”, as well as the tropical Pacific annual mean state in mid-Pliocene and pre-industrial simulations. Results show a reduced ENSO amplitude in the model-ensemble mean (−24 %) with respect to the pre-industrial, with 15 out of 17 individual models showing such a reduction. Furthermore, the spectral power of this variability considerably decreases in the 3–4-year band. The spatial structure of the dominant empirical orthogonal function shows no particular change in the patterns of tropical Pacific variability in the model-ensemble mean, compared to the pre-industrial. Although the time-mean zonal SST gradient in the equatorial Pacific decreases for 14 out of 17 models (0.2 ∘C reduction in the ensemble mean), there does not seem to be a correlation with the decrease in ENSO amplitude. The models showing the most “El Niño-like” mean state changes show a similar ENSO amplitude to that in the pre-industrial reference, while models showing more “La Niña-like” mean state changes generally show a large reduction in ENSO variability. The PlioMIP2 results show a reasonable agreement with both time-mean proxies indicating a reduced zonal SST gradient and reconstructions indicating a reduced, or similar, ENSO variability.
mid-Pliocene warm period↗
Climate-Driven Divergence in Biophysical and Economic Impacts of Agrivoltaics
Increasing global demands for food and energy necessitate innovative land-use solutions. Agrivoltaics, colocating solar photovoltaics with agriculture, shows promise, but its widespread adoption faces complex biophysical and economic trade-offs in a changing climate. Here, we develop an integrated biophysical-economic modeling framework to quantify how agrivoltaics affect biophysical and economic impacts across the Midwestern United States under both current and project climate conditions. We find strong regional divergences driven by climate gradients. In the humid eastern Midwest, solar panel shading limits photosynthesis, leading to reduced yields (maize -24%; soybean -16%) and lower farmers' profitability (maize -16%; soybean -2%) compared to conventional agriculture. Conversely, in the semiarid western region, shading alleviates heat and water stress, moderating yield reductions for maize (-12%) and even boosting soybean yields (+6%), resulting in improved economic returns (-6% for maize; +9% for soybean), for a scenario with 33% photovoltaic ground coverage ratio. Although agrivoltaics generate substantial electrical energy across all regions, high upfront installation costs challenge solar developers compared to standalone solar photovoltaics. However, our analysis identifies “win-win” opportunities where soybean-based agrivoltaics in the semiarid region produce economic benefits for both farmers and solar developers, highlighting the necessity for region-specific designs tailored to local climate conditions. Critically, future climate projections indicate eastward expansion of semiarid conditions, broadening areas where agrivoltaics can mitigate crop yield penalties (even boosting yield) and improve overall profitability, especially under high-emission scenarios. The results provide a mechanistic and economically integrated understanding essential for developing evidence-based and region-specific strategies to scale agrivoltaics in a changing climate.
14 SOLAR ENERGY↗
A finite micro-rotation material point method for micropolar solid and fluid dynamics with three-dimensional evolving contacts and free surfaces
This paper introduces an explicit material point method designed specifically for simulating the micropolar continuum dynamics in the finite deformation and finite microrotation regime. The material point method enables us to simulate large deformation problems while circumventing the potential mesh distortion without remeshing. To eliminate rotational motion damping and loss of angular momentum during the projection, we introduce the mapping for microinertia and angular momentum between particles and grids through the affine particle-in-cell approach. The microrotation and the curvature at each particle are updated through zero-order forward integration of the microgyration and its spatial gradient. We show that the microinertia and the angular momentum are conserved during the projections between particles and grids in our formulation. We verify the formulation and implementation by comparing with the analytical dispersion relation of micropolar waves under the small strain and small microrotation, as well as the analytical soliton solution for solids undergoing large deformation and large microrotation. Additionally we also demonstrate the capacity of the proposed computational framework to handle a wide spectrum of simulations that exhibit size effects in the geometrical nonlinear regime through three representative numerical examples, i.e., a cantilever beam torsion problem, a fragment-impact penetration problem, and a micropolar fluid discharging problem.
42 ENGINEERING↗
Late growth of early-type galaxies in low-z massive clusters
ABSTRACT We study a sample of 936 early-type galaxies (ETGs) located in 48 low-z regular galaxy clusters with M200 ≥ 1014 M⊙ at z < 0.1. We examine variations in the concentration index, radius, and colour gradient of ETGs as a function of their stellar mass and loci in the projected phase space (PPS) of the clusters. We aim to understand the environmental influence on the growth of ETGs according to the time since infall into their host clusters. Our analysis indicates a significant change in the behaviour of the concentration index C and colour gradient around $M_{\ast } \approx 2\times 10^{11} ~M_\odot \equiv \tilde{M}_{\ast }$. Objects less massive than $\tilde{M}_{\ast }$ present a slight growth of C with M*, with negative and approximately constant colour gradients in all regions of the PPS. Objects more massive than $\tilde{M}_{\ast }$ present a slight decrease of C with M*, with colour gradients becoming less negative and approaching zero. We also find that objects more massive than $\tilde{M}_{\ast }$, in all PPS regions, have smaller R90 for a given R50, suggesting a smaller external growth in these objects or even a shrinkage possibly due to tidal stripping. Finally, we estimate different dark matter fractions for galaxies in different regions of the PPS, with the ancient satellites having the largest fractions, fDM ≈ 65 per cent. These results favour a scenario where cluster ETGs experience environmental influence the longer they remain and the deeper into the gravitational potential they lie, indicating a combination of tidal stripping + harassment, which predominate during infall, followed by mergers + feedback effects affecting the late growth of ancient satellites and BCGs.
Astronomy & Astrophysics↗
Ka-band linearizer for the Ultra-Compact X-ray free-electron laser at UCLA
There is a strong demand for accelerating structures able to achieve higher gradients and more compact dimensions for the next generation of linear accelerators for research, industrial and medical applications. Notably innovative technologies will permit compact and affordable advanced accelerators as the linear collider and X-ray free-electron lasers (XFELs) with accelerating gradients over twice the value achieved with current technologies. In particular XFELs are able to produce coherent X-ray pulses with peak brightness 10 orders of magnitude greater than preceding approaches, which has revolutionized numerous research fields through imaging of the nanoscopic world at the time and length scale of atom-based systems, that is of femtosecond and Angstrom. There is a strong interest for combining these two fields, to form a proper tool with the goal of producing a very compact XFEL in order to investigate multi-disciplinary topics in chemistry, biology, materials science, medicine and physics. In the framework of the Ultra-Compact XFEL project under study at the University of California, Los Angeles, a high gradient radio-frequency accelerating structure for the longitudinal phase-space linearization with an integrated voltage of at least 15 MV working on 6th harmonic of the main Linac frequency is required. We here present the electromagnetic design of a cryogenic normal-conducting 8 cm long Ka-band standing-wave linearizer working on π mode with a target accelerating gradient beyond 100 MV/m. The studies have been performed analytically and numerically to investigate the beam dynamics and electromagnetic issues.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗