Search NASA⌕ Search

SEARCH · Search NASA

Results for “Memory safety”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

Lamellar: A Rust-based Asynchronous Tasking and PGAS Runtime for High Performance Computing

Cybersecurity is one of the largest concerns in modern computing, impacting and dictating how governments, private corporations, and individuals interact with and live in an increasingly digital world. The NSA has recently released a memo [ 1] on “Software Memory Safety” where they highlight that both Microsoft and Google have stated around 70% of software vulnerabilities were due to memory safety issues. Although languages such as C and C++ provide freedom and flexibility with memory management, guaran- teeing safety falls mostly on the developer. The NSA recommends using “memory safe” languages whenever possible. In this paper we introduce Lamellar, an asynchronous tasking and PGAS HPC runtime written in Rust, one such "memory safe" language. We describe the entire Lamellar stack, from network interfaces to high- level abstractions such as distributed LamellarArrays and Active Messages. We conclude by showing comparable performance to legacy PGAS runtimes (e.g. OpenSHMEM) on a subset of the BALE kernel suite while maintaining strong memory safety principles.

HPC Software Systems, Rust Programming Language, P↗

Software stewardship and advancement of a high-performance computing scientific application: QMCPACK

Here, we provide an overview of the software engineering efforts and their impact in QMCPACK, a production-level ab-initio Quantum Monte Carlo open-source code targeting high-performance computing (HPC) systems. Aspects included are: (i) strategic expansion of continuous integration (CI) targeting CPUs, using GitHub Actions own runners, and NVIDIA and AMD GPUs used in pre-exascale systems, (ii) incremental reduction of memory leaks using sanitizers, (iii) incorporation of Docker containers for CI and reproducibility, and (iv) refactoring efforts to improve maintainability, testing coverage, and memory lifetime management. We quantify the value of these improvements by providing metrics to illustrate the shift towards a predictive, rather than reactive, maintenance approach. Our goal, in documenting the impact of these efforts on QMCPACK, is to contribute to the body of knowledge on the importance of research software engineering (RSE) for the stewardship and advancement of community HPC codes to enable scientific discovery at scale.

97 MATHEMATICS AND COMPUTING↗

POSTER: Automatic Differentiation of Parallel Loops with Formal Methods

The accompanying poster to this short paper presents a combination of reverse mode AD and formal methods to enable efficient differentiation of (or backpropagation through) shared-memory parallel code. Compared to the state of the art, our approach can more often avoid the need for atomic updates or private data copies during the parallel derivative computation, even in the presence of unstructured or data-dependent data access patterns. This is achieved by gathering information about the memory access patterns from the input program, which is assumed to be correctly parallelized. This information is then used to build a model of assertions in a theorem prover, which can be used to check the safety of shared memory accesses during the parallel derivative computation

Automatic Differentiation↗

Multifunctional Fiber-Reinforced Polymer Composites for Damage Detection and Memory

Self-structural health monitoring (SHM) functionalities for fiber-reinforced polymer composites have become highly sought after to ensure the structural safety of newly advancing components in the automotive, civil, mechanical, and aerospace industries. This paper introduces a self-damage detection and memory (SDDM) hybrid composite material, where the structural carbon fiber tow is transformed into a piezoresistive sensor network, and the structural glass fiber operates as electrical insulation. In this study, SDDM specimens were fabricated, and tensile and impact tests were performed. The tensile tests of SDDM specimens find two distinct loading peaks: first where the carbon fiber fails, and second where the glass fiber fails. A linear correlation was observed between the carbon fiber resistance and composite strain up to a threshold, beyond which a sharp nonlinear increase in resistance occurred. The resistance then approached infinity, coinciding with the first loading peak and failure of the carbon fiber elements. This demonstrates the potential for a damage early warning threshold. Additionally, the effect of stitching the sensor tow in a zig-zag pattern over a large area was investigated using tailored fiber placement (TFP) of 1-loop, 3-loop, and 5-loop specimens. Tensile testing found that increasing the number of loops improved the sensor’s accuracy for strain sensing. Furthermore, impact tests were conducted, and as the impact energy progressively increased, the sensor resistance permanently increased. This illustrates a capability for self-memory of microdamage throughout the life cycle of the structure, potentially useful for predicting the remaining life of the composite.

Demo, Luke B. (ORCID:0000000208806522)↗

In Situ/Operando (Soft) X-ray Spectroscopy Study of Beyond Lithium-ion Batteries

The lightweight, rechargeable lithium-ion battery is one of the dominant energy storage devices globally in portable electronics due to its high energy density, no memory effect, wide operating voltage, lightweight, and good charge efficiency. However, due to safety concerns, the depletion of lithium reserves, and the corresponding increase of cost, an alternative battery system becomes more and more desirable. To develop alternative battery systems with low cost and high material abundance, for example, sodium, magnesium, zinc, and calcium, it is important to understand the chemical and electronic structure of materials. Additionally, soft X-ray spectroscopy, for example, X-ray absorption spectroscopy (XAS), X-ray emission spectroscopy (XES), and resonant inelastic soft X-ray scattering (RIXS), is an element-specific technique with sensitivity to the local chemical environment and structural order of the element of interest. Modern soft X-ray systems enable operando experiments that can be applied to amorphous and crystalline samples, making it a powerful tool for studying the electronic and structural changes in electrode and electrolyte species. In this article, the application of in situ/operando (soft) X-ray spectroscopy in beyond lithium-ion batteries is reviewed to demonstrate how such spectroscopic characterizations could facilitate the interpretation of interfacial phenomena under in situ/operando condition and subsequent development of the beyond lithium-ion batteries.

(soft) X-ray spectroscopy↗

Domain-Specific Type-Safe APIs for Hierarchical Scientific Data with Modern C++

General-purpose library application programming interfaces (APIs) for self-describing hierarchical scientific data storage, such as the HDF5 and NetCDF libraries, are traditionally of runtime nature. Runtime errors for entry existence and data types are typically caught later in the development process of higher-level application-specific APIs. In this paper, we propose exploiting modern C++ metaprogramming features to add compile-time type-safety to improve the interaction with a well-defined metadata-rich scientific schema in domain-specific hierarchical datasets. We tackle two aspects of common use: (i) direct data access, (ii) flexible “in-memory” index models for efficient search and data processing. The proposed APIs use C++17’s template type auto deduction features, C++11’s enum class for type-safety and C-style preprocessor macros for generative templated code. We showcase the pros and cons of our initial work on the standard NeXus schema used for annotating and storing experimental neutron scattering data at several facilities around the world on top of HDF5. Extendable compile-time type-safe APIs are a desirable feature that could be indexed by any modern integrated development environment (IDE). Hence, such APIs can help ease the learning curve for domain scientists using a less error-prone software interaction to enhance the findability of their data without resorting to a domain-specific language (DSL).

Godoy, William↗

Performance Evaluation of Different Parallel Programming Models in SCALE-Shift Sequences for Criticality and Shielding Applications [Abstract]

The SCALE code system has been widely used for nuclear criticality safety, reactor physics, radiation shielding, source term generation, and inventory analyses by researchers, industry, and regulatory bodies. Although limited support for shared- and distributed-memory parallel processing was introduced via C++ threading, OpenMP, and MPI, a hybrid parallel programming model with both distributed- and shared-memory parallelism has not been fully supported in the SCALE code system.

Nuclear Criticality Safety Program (NCSP)↗

Cognitive Aging as a Human Factor: Effects of Age on Human Performance

Nuclear power plant (NPP) control room operators must make ongoing computations and decisions that maximize production and ensure safety, which places a high cognitive burden on the operators. How cognitions such as attention, visuospatial ability, and working memory interact with socio-technical systems to achieve optimal operations is well studied. However, there is an absence of research that examines how cognitive functioning within the NPP control room environment is moderated by developmental aging processes. This is of critical importance because different types of cognitive actions are known to develop and peak at different times across the adult life span, and it is becoming increasingly clear that there is no age at which all cognitive faculties operate at maximum capacity. Thus, given that NPPs are experiencing an aging workforce, it is vital to identify how mission critical cognitions change with age. This paper reviews implications of aging on reactor operators in the current and new fleet. We highlight lessons that can be learned from state-of-the-art human factors research that considers aging, lessons from the large cognitive aging literature, and lessons from aging workers in other industries that use sophisticated socio-technical systems, such as aviation. We also consider the important subject of aging effects versus expertise and present preliminary data that support the premise that age of operator is linked to effective and efficient operations but that this relationship may be moderated by level of operations expertise. In conclusion, we apply these lessons to future considerations for aging research in current nuclear operations and with the advent of advanced modernized control rooms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Phase IB study of ziv-aflibercept plus pembrolizumab in patients with advanced solid tumors

Background The combination of antiangiogenic agents with immune checkpoint inhibitors could potentially overcome immune suppression driven by tumor angiogenesis. We report results from a phase IB study of ziv-aflibercept plus pembrolizumab in patients with advanced solid tumors. Methods This is a multicenter phase IB dose-escalation study of the combination of ziv-aflibercept (at 2–4 mg/kg) plus pembrolizumab (at 2 mg/kg) administered intravenously every 2 weeks with expansion cohorts in programmed cell death protein 1 (PD-1)/programmed death-ligand 1(PD-L1)-naïve melanoma, renal cell carcinoma (RCC), microsatellite stable colorectal cancer (CRC), and ovarian cancer. The primary objective was to determine maximum tolerated dose (MTD) and recommended dose of the combination. Secondary endpoints included overall response rate (ORR) and overall survival (OS). Exploratory objectives included correlation of clinical efficacy with tumor and peripheral immune population densities. Results Overall, 33 patients were enrolled during dose escalation (n=3) and dose expansion (n=30). No dose-limiting toxicities were reported in the initial dose level. Ziv-aflibercept 4 mg/kg plus pembrolizumab 2 mg/kg every 2 weeks was established as the MTD. Grade ≥3 adverse events occurred in 19/33 patients (58%), the most common being hypertension (36%) and proteinuria (18%). ORR in the dose-expansion cohort was 16.7% (5/30, 90% CI 7% to 32%). Complete responses occurred in melanoma (n=2); partial responses occurred in RCC (n=1), mesothelioma (n=1), and melanoma (n=1). Median OS was as follows: melanoma, not reached (NR); RCC, 15.7 months (90% CI 2.5 to 15.7); CRC, 3.3 months (90% CI 0.6 to 3.4); ovarian, 12.5 months (90% CI 3.8 to 13.6); other solid tumors, NR. Activated tumor-infiltrating CD8 T cells at baseline (CD8+PD1+), high CD40L expression, and increased peripheral memory CD8 T cells correlated with clinical response. Conclusion The combination of ziv-aflibercept and pembrolizumab demonstrated an acceptable safety profile with antitumor activity in solid tumors. The combination is currently being studied in sarcoma and anti-PD-1-resistant melanoma. Trial registration number NCT02298959 .

Rahma, Osama E.↗

Oxidation Behavior and Property Degradation of Nuclear Graphites

During its multidecade operation in the core of nuclear reactors, graphite components are subjected to aggressive and continuous exposure to a high field of ionizing and neutron irradiation, high temperature, and various types of present and postulated chemical attacks. High density, high crystallinity polygranular synthetic graphite is unique among other materials for its extraordinary capacity of resisting and adapting to the aggression inflicted by high temperature, high energy neutron bombardment and ionizing gamma radiation. But, as a carbonaceous material, even though of very high purity, graphite is reactive towards common oxidizing agents: oxygen, carbon dioxide, water. Safe operation of HTGRs relies, among other aspects, on engineered safeguard systems for efficient and continuous protection of graphite components against oxidation. Graphite oxidation behavior was, and continues to be, an important direction of theoretical and experimental research, engineering analyses, models and simulations, and design and safety regulations. The avalanche of publications, reports, experimental data, computer codes, and regulatory documents related to oxidation behavior of nuclear graphite is now accelerating to new levels, prompted by the increased interest for nuclear energy as a clean, carbon-free energy source. Even though public’s perception of nuclear energy advantages may still be influenced by the memories of past accidents of nuclear reactors from generations II and III, the community of informed scientists and engineers, regulators and statemen knows that generation IV of nuclear reactors is designed at very high safety standards, doubled by great advances of scientific knowledge and technological progress. One of routes of these recent advances is directed at better understanding of graphite oxidation behavior, its relationship with graphite manufacturing and microstructural properties, along with the effects of various environmental factors and process variables. Together, the recent progress in manufacturing, properties characterization, and modeling of intricated physical and chemical processes that concur to the oxidation behavior led to development of powerful simulation codes able to analyze various scenarios of normal operation and hypothetical off-normal events, and thus to clearly specify the allowable parameters envelopes for the designers, constructors, and operators of current and future modular HTGRs. This review begins with an introduction on manufacturing methods, structure, and properties of nuclear graphite, including basic requirements that this specialty graphite type must satisfy for nuclear use. It continues with a chapter on environmental effects on nuclear graphite, where emphasis is placed less on irradiation and much more on oxidation phenomena, their safety implications, and the basic traits of chronic and acute oxidation by air (oxygen) and water (humidity, steam). Particular attention is placed on the three graphite grades of interest for this document (IG-110, NBG-18, PCEA). A chapter on properties degradation induced by oxidation follows, with focus on density, dimensional, and mechanical properties changes. The next chapter is intended as a brief review of various approaches used for modeling of graphite oxidation behavior. It summarizes the progress of oxidation models, from the early attempts to complex computational approaches interfaced with specialized computer codes designed for nuclear reactor simulations. Last, a list is presented of knowledge gaps where more research is needed. A short summary concludes the review.

36 MATERIALS SCIENCE↗

Accurate Compression of Tabulated Chemistry Models with Partition of Unity Networks

Tabulated chemistry models are widely used to simulate large-scale turbulent fires in applications including energy generation and fire safety. Tabulation via piecewise Cartesian interpolation suffers from the curse-of-dimensionality, leading to a prohibitive exponential growth in parameters and memory usage as more dimensions are considered. Artificial neural networks (ANNs) have attracted attention for constructing surrogates for chemistry models due to their ability to perform high-dimensional approximation. However, due to well-known pathologies regarding the realization of suboptimal local minima during training, in practice they do not converge and provide unreliable accuracy. Partition of unity networks (POUnets) are a recently introduced family of ANNs which preserve notions of convergence while performing high-dimensional approximation, discovering a mesh-free partition of space which may be used to perform optimal polynomial approximation. In this work, we assess their performance with respect to accuracy and model complexity in reconstructing unstructured flamelet data representative of nonadiabatic pool fire models. Our results show that POUnets can provide the desirable accuracy of classical spline-based interpolants with the low memory footprint of traditional ANNs while converging faster to significantly lower errors than ANNs. For example, we observe POUnets obtaining target accuracies in two dimensions with 40 to 50 times less memory and roughly double the compression in three dimensions. We also address the practical matter of efficiently training accurate POUnets by studying convergence over key hyperparameters, the impact of partition/basis formulation, and the sensitivity to initialization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling injection-induced fault slip using long short-term memory networks

Stress changes due to changes in fluid pressure and temperature in a faulted formation may lead to the opening/shearing of the fault. This can be due to subsurface (geo)engineering activities such as fluid injections and geologic disposal of nuclear waste. Such activities are expected to rise in the future making it necessary to assess their short- and long-term safety. Here, a new machine learning (ML) approach to model pore pressure and fault displacements in response to high-pressure fluid injection cycles is developed. The focus is on fault behavior near the injection borehole. To capture the temporal dependencies in the data, long short-term memory (LSTM) networks are utilized. To prevent error accumulation within the forecast window, four critical measures to train a robust LSTM model for predicting fault response are highlighted: (i) setting an appropriate value of LSTM lag, (ii) calibrating the LSTM cell dimension, (iii) learning rate reduction during weight optimization, and (iv) not adopting an independent injection cycle as a validation set. Several numerical experiments were conducted, which demonstrated that the ML model can capture peaks in pressure and associated fault displacement that accompany an increase in fluid injection. The model also captured the decay in pressure and displacement during the injection shut-in period. Further, the ability of an ML model to highlight key changes in fault hydromechanical activation processes was investigated, which shows that ML can be used to monitor risk of fault activation and leakage during high pressure fluid injections.

58 GEOSCIENCES↗

Nuclear Direct Air Capture with Carbon Storage (NuDACCS) (Final Technical Report)

This final report, which is for DOE Award Number DE-FE0032160 (Direct Air Capture Combined with dedicated Long-Term Carbon Storage, Coupled to Existing Low-Carbon Energy), covers the Nuclear Direct Air Capture with Carbon Storage (NuDACCS) project period of performance from 03/31/2022 to 12/27/2024. Battelle Memorial Institute (Battelle) partnered with Aircapture LLC (Aircapture), Southern Company (Southern), Carbonvert, the University of Alabama, and Sargent & Lundy (S&L) to develop a front end engineering design (FEED) study for a direct air capture (DAC) system co-located with Southern Company's Joseph M. Farley Nuclear Plant (Plant Farley) in Columbia, Alabama. The DAC system was designed to capture at least 5,000 net tonnes of carbon dioxide (CO2) per year from ambient air in a form suitable for long duration carbon storage (e.g., geologic storage). To complement and support the FEED study, additional analyses were completed, including a Technology Maturation Plan (TMP); Workforce Readiness Plan; Project Cost Estimate; Business Case Analysis (BCA); Life Cycle Analysis (LCA); Environmental Health and Safety (EH&S) Assessment; and Environmental Justice (EJ) Analysis and Economic Revitalization and Job Creation Outcomes Analysis.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Shotgun Immunoproteomic Approach for the Discovery of Linear B-Cell Epitopes in Biothreat Agents Francisella tularensis and Burkholderia pseudomallei

Peptide-based subunit vaccines are coming to the forefront of current vaccine approaches, with safety and cost-effective production among their top advantages. Peptide vaccine formulations consist of multiple synthetic linear epitopes that together trigger desired immune responses that can result in robust immune memory. The advantages of linear compared to conformational epitopes are their simple structure, ease of synthesis, and ability to stimulate immune responses by means that do not require complex 3D conformation. Prediction of linear epitopes through use of computational tools is fast and cost-effective, but typically of low accuracy, necessitating extensive experimentation to verify results. On the other hand, identification of linear epitopes through experimental screening has been an inefficient process that requires thorough characterization of previously identified full-length protein antigens, or laborious techniques involving genetic manipulation of organisms. In this study, we apply a newly developed generalizable screening method that enables efficient identification of B-cell epitopes in the proteomes of pathogenic bacteria. As a test case, we used this method to identify epitopes in the proteome of Francisella tularensis (Ft), a Select Agent with a well-characterized immunoproteome. Our screen identified many peptides that map to known antigens, including verified and predicted outer membrane proteins and extracellular proteins, validating the utility of this approach. We then used the method to identify seroreactive peptides in the less characterized immunoproteome of Select Agent Burkholderia pseudomallei (Bp). This screen revealed known Bp antigens as well as proteins that have not been previously identified as antigens. Although B-cell epitope prediction tools Bepipred 2.0 and iBCE-EL classified many of our seroreactive peptides as epitopes, they did not score them significantly higher than the non-reactive tryptic peptides in our study, nor did they assign higher scores to seroreactive peptides from known Ft or Bp antigens, highlighting the need for experimental data instead of relying on computational epitope predictions alone. The present workflow is easily adaptable to detecting peptide targets relevant to the immune systems of other mammalian species, including humans (depending upon the availability of convalescent sera from patients), and could aid in accelerating the discovery of B-cell epitopes and development of vaccines to counter emerging biological threats.

60 APPLIED LIFE SCIENCES↗

Safety and efficacy of C. muridarum vaccines adjuvanted with CpG-1826 and four concentrations of Montanide-ISA-720-VG

It is recommended that the adjuvant Montanide ISA 720 VG be used at a concentration of 70% v/v. At this concentration, Montanide causes at the site of immunization a local granuloma that can last for several weeks. To determine the safety and protective efficacy of a Chlamydia muridarum MOMP vaccine, formulated with CpG-1826 and four different concentrations of Montanide (70%, 50%, 30% and 10%), BALB/c (H-2 d ) female mice were immunized twice intramuscularly. Local reactogenicity was significant for vaccines formulated with 70% or 50% Montanide but not for those inoculated with 30% or 10% Montanide. Robust humoral and cell mediated memory immune responses were elicited by the 70%, 50% and 30% Montanide formulations. Mice were challenged intranasally with 10 4 C. muridarum inclusion forming units (IFU). Based on changes in body weight, lungs’s weight and number of IFU recovered, mice vaccinated with the 70%, 50% and 30% Montanide formulations were significantly protected, but not mice receiving 10% Montanide. To conclude, we recommend the 30% Montanide concentration to be tested in humans and animal models to determine its safety and efficacy, in comparison to the 70% Montanide concentration currently used. The 30% Montanide formulation could significantly facilitate licensing of this adjuvant for human use.

60 APPLIED LIFE SCIENCES↗

Conditional Point Sampling: A Monte Carlo Method for Radiation Transport in Stochastic Media.

Current methods for stochastic media transport are either computationally expensive or, by nature, approximate. Moreover, none of the well-developed, benchmarked approximate methods can compute the variance caused by the stochastic mixing, a quantity especially important to safety calculations. Therefore, we derive and apply a new conditional probability function (CPF) for use in the recently developed stochastic media transport algorithm Conditional Point Sampling (CoPS), which 1) leverages the full intra-particle memory of CoPS to yield errorless computation of stochastic media outputs in 1D, binary, Markovian-mixed media, and 2) leverages the full inter-particle memory of CoPS and the recently developed Embedded Variance Deconvolution method to yield computation of the variance in transport outputs caused by stochastic material mixing. Numerical results demonstrate errorless stochastic media transport as compared to reference benchmark solutions with the new CPF for this class of stochastic mixing as well as the ability to compute the variance caused by the stochastic mixing via CoPS. Using previously derived, non-errorless CPFs, CoPS is further found to be more accurate than the atomic mix approximation, Chord Length Sampling (CLS), and most of memory-enhanced versions of CLS surveyed. In addition, we study the compounding behavior of CPF error as a function of cohort size (where a cohort is a group of histories that share intra-particle memory) and recommend that small cohorts be used when computing the variance in transport outputs caused by stochastic mixing.

61 RADIATION PROTECTION AND DOSIMETRY↗

Implementation of Triply Periodic Minimal Surfaces (TPMS) as surface objects in OpenMC

Triply Periodic Minimal Surfaces (TPMS) represent a promising geometry for future fuel designs due to their significant surface-to-volume ratio, which facilitates efficient cooling of nuclear fuel, a crucial factor for safety and efficiency. Demonstrating the remarkable capabilities of TPMS fuel requires initial modeling and simulation. This paper presents an implementation of TPMS in the Monte Carlo code OpenMC, enabling reactor physics modeling of TPMS. Here, the primary advantages over traditional methods using CAD files include reduced memory requirements for computations and high-fidelity implementation. This implementation has been tested against CAD files loaded in Serpent2, yielding promising results with low biases in the $k_{\textrm{eff}}$, comparable to biases in the material balance sheet. The implementation presented in this work will be used in future reactor physics computations related to new reactor designs involving TPMS-based fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels (Final Scientific/Technical Report)

The project, "Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels," represents a significant advancement in nuclear fuel recycling technology. It integrates cutting-edge multimodal sensor fusion, machine learning (ML), and digital twin (DT) technologies to address challenges in material safeguarding, process optimization, and regulatory compliance for pyroprocessing facilities. This research has significantly enhanced the understanding of pyrochemical fuel recycling processes by developing innovative tools and methodologies. The Multimodal Safeguards Monitoring Unit (MSMU) combines electroanalytical techniques, Raman spectroscopy, and differential thermal analysis (DTA) to enable high-fidelity, near-real-time material accountancy measurements. Machine learning techniques, such as Long Short-Term Memory (LSTM) autoencoders, are utilized to detect anomalies in material balances and sensor data, improving the reliability of safeguards monitoring. Additionally, digital twin technology has been established to provide real-time system-level monitoring and diagnostics, integrating physics-based models with sensor data to optimize process safety and efficiency.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗