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At least 361 records · Page 20

Molecular Dynamics Modeling of Carbon Nanotube Composite Fracture Using ReaxFF

Carbon nanotube (CNT) fiber reinforced composites with specific tensile strengths and moduli approaching those of aerospace grade carbon fiber composites have recently been reported. This achievement was enabled by the emerging availability of high N/tex yarns in kilometer-scale quantities. While the production of this yarn is an impressive advance, its strength is still much lower than that of the individual CNTs comprising the yarn. Closing this gap requires understanding load transfer between CNTs at the nanometer dimensional scale. This work uses reactive molecular dynamics simulations to gain an understanding at the nanometer scale of the key factors that determine CNT nanocomposite mechanical performance, and to place more realistic upper bounds on the target properties. While molecular dynamics simulations using conventional force fields can predict elastic properties, the ReaxFF reactive forcefield can also model fracture behavior because of its ability to accurately describe bond breaking and formation during a simulation. The upper and lower bounds of CNT composite properties are investigated by comparing systems composed of CNTs continuously connected across the periodic boundary with systems composed of finite length CNTs. These lengths, effectively infinite for the continuous tubes and an aspect ratio of 13 for the finite length case, result from practical limitations on the number of atoms that can be included in a simulation. Experimentally measured aspect ratios are typically on the order of 100,000, so the calculated results should represent upper and lower limits on experimental mechanical properties. Finally, the effect of various degrees of covalent crosslinking between the CNTs and amorphous carbon matrix is considered to identify the amount of CNT-matrix covalent bonding that maximizes overall composite properties.

Jensen, Benjamin D.↗

Limitations of Fault-Tolerant Quantum Linear System Solvers for Quantum Power Flow

Quantum computers hold promise for solving problems intractable for classical computers, especially those with high time or space complexity. Practical quantum advantage can be said to exist for such problems when the end-to-end time for solving such a problem using a classical algorithm exceeds that required by a quantum algorithm. Reducing the power flow (PF) problem into a linear system of equations allows for the formulation of quantum PF (QPF) algorithms, which are based on solving methods for quantum linear systems such as the Harrow-Hassidim-Lloyd (HHL) algorithm. Speedup from using QPF algorithms is often claimed to be exponential when compared to classical PF solved by state-of-the-art algorithms. Here, we investigate the potential for practical quantum advantage in solving QPF compared to classical methods on gate-based quantum computers. Notably, this paper does not present a new QPF solving algorithm but scrutinizes the end-to-end complexity of the QPF approach, providing a nuanced evaluation of the purported quantum speedup in this problem. Our analysis establishes a best-case bound for the HHL-based quantum power flow complexity, conclusively demonstrating that the HHL-based method has higher runtime complexity compared to the classical algorithm for solving the direct current power flow (DCPF) and fast decoupled load flow (FDLF) problem. Notably, our analysis and conclusions can be extended to any quantum linear system solver with rigorous performance guarantees, based on the known complexity lower bounds for this problem. Additionally, we establish that for potential practical quantum advantage (PQA) to exist it is necessary to consider DCPF-type problems with a very narrow range of condition number values and readout requirements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Characterization of International Space Station Crew Members' Workload Contributing to Fatigue, Sleep Disruption and Circadian De-synchronization

The focus of this paper is to characterize how the International Space Station (ISS) crewmembers’ workload may be contributing to sleep loss, circadian misalignment and fatigue. Both sleep quantity and subjective sleep quality are reduced in ISS crewmembers (Barger, Flynn-Evans, Kubey, Walsh, Ronda, Wang, Wright, & Czeisler, 2014). Evidence indicates that the use of hypnotic drugs does not appear to promote extended sleep duration. Because sleep is often driven by psychosocial as well as somatic attributes, traditional therapies may only partially moderate the problem for some individuals. Accordingly, searching for additional abatement tactics is a sensible plan. Scientific studies have shown that sleep can be disrupted from work-related stressors. On the ISS, to optimize their time, the crewmembers follow prescribed, ambitious and rigorous schedules with shared deadlines. Here it will be argued that these human capital leveraging techniques may be undermining the astronaut’s sleep, which could negatively impact performance. Along with half of the Earth-bound working population (Paoli & Merllié, 2001), ISS crewmembers may not be adequately recovering from their workload. This paper begins with a characterization of the working conditions of ISS crewmembers, describes the development of rigorous schedules and portrays a typical workday. Terrestrially-based research is compiled to describe how full and partial sleep deprivation affect physical and cognitive performance and how ISS work characteristics may disrupt sleep and subsequent performance. The literature points toward potential solutions to astronaut fatigue that is related to their workload. Finally, throughout the text, evidence is provided from semi-structured interviews, biographies and textual databases to support the argument that astronaut workload is contributing to their sleep loss and fatigue and that research, development and mitigation strategies should focus on enhancing the restorative process.

fatigue↗

Self-Sacrificial Template Synthesis of Fe-N-C Catalysts with Dense Active Sites Deposited on A Porous Carbon Network for High Performance in PEMFC

In this study, iron-nitrogen-carbon (Fe-N-C) single-atom catalysts are promising sustainable alternatives to the costly and scarce platinum (Pt) to catalyze the oxygen reduction reactions (ORR) at the cathode of proton exchange membrane fuel cells (PEMFCs). However, Fe-N-C cathodes for PEMFC are made thicker than Pt/C ones, in order to compensate for the lower intrinsic ORR activity and site density of Fe-N-C materials. The thick electrodes are bound with mass transport issues that limit their performance at high current densities, especially in H 2 /air PEMFCs. Practical Fe-N-C electrodes must combine high intrinsic ORR activity, high site density, and fast mass transport. Herein, it has achieved an improved combination of these properties with a Fe-N-C catalyst prepared via a two-step synthesis approach, constructing first a porous zinc-nitrogen-carbon (Zn-N-C) substrate, followed by transmetallating Zn by Fe via chemical vapor deposition. A cathode comprising this Fe-N-C catalyst has exhibited a maximum power density of 0.53 W cm -2 in H 2 /air PEMFC at 80 °C. The improved power density is associated with the hierarchical porosity of the Zn-N-C substrate of this work, which is achieved by epitaxial growth of ZIF-8 onto g-C 3 N 4 , leading to a micro-mesoporous substrate.

25 ENERGY STORAGE↗

Challenges in Qualification of Thermal Protection Systems in Extreme Entry Environments

Planetary entry vehicles employ ablative TPS materials to shield the aeroshell from entry aeroheating environments. To ensure mission success, it must be demonstrated that the heat shield system, including local features such as seams, does not fail at conditions that are suitably margined beyond those expected in flight. Furthermore, its thermal response must be predictable, with acceptable fidelity, by computational tools used in heat shield design. Mission assurance is accomplished through a combination of ground testing and material response modelling. A material's robustness to failure is verified through arcjet testing while its thermal response is predicted by analytical tools that are verified against experimental data. Due to limitations in flight-like ground testing capability and lack of validated high-fidelity computational models, qualification of heat shield materials is often achieved by piecing together evidence from multiple ground tests and analytical simulations, none of which fully bound the flight conditions and vehicle configuration. Extreme heating environments (>2000 W/sq. cm heat flux and >2 atm pressure), experienced during entries at Venus, Saturn and Ice Giants, further stretch the current testing and modelling capabilities for applicable TPS materials. Fully-dense Carbon Phenolic was the material of choice for these applications; however, since heritage raw materials are no longer available, future uses of re-created Carbon Phenolic will require re-qualification. To address this sustainability challenge, NASA is developing a new dual-layer material based on 3D weaving technology called Heat shield for Extreme Entry Environments (HEEET). Regardless of TPS material, extreme environments pose additional certification challenges beyond what has been typical in recent NASA missions. Scope of this presentation: This presentation will give an overview of challenges faced in verifying TPS performance at extreme heating conditions. Examples include: (1) Bounding aeroheating parameters (heat flux, pressure, shear and enthalpy) in ground facilities. How to certify TPS if environments can't be bounded or aeroheating parameters can't be simultaneously achieved. (2) Higher uncertainties in ground test environments (facility calibration and analytical predictions) at extreme conditions. (3) Testing in flows similar to planetary atmosphere composition (H2/He for Gas and Ice Giants). (4) Test sample size limitations for qualifying seam designs. (5) Lack of computational tools capable of simulating all significant aspects of TPS performance (including initiation and propagation of failures). This presentation will provide recommendations on how the EDL community can address these challenges and mitigate some of the risks involved in flying TPS materials at extreme conditions. Examples include: (1) Dedicated activity to understanding TPS failure modes. Develop computational tools capable of modelling fluid interaction with material's thermostructural response. Validate these tools through failure testing. A better understanding of failure mechanisms may eliminate the need to fully bound all aeroheating parameters in ground testing. (2) Enhancements to current testing facilities to simulate flight-like ablation mechanism (ex. testing in Nitrogen at Ames Interaction Heating Facility to limit oxidation in favor of more sublimation). (3) Improved characterization of test conditions with new diagnostic methods and determination of environment uncertainty through rigorous statistical analysis of available data. (4) Design margin policies that are directly tied to uncertainties in ground test environments and modelling fidelity

Mahzari, Milad↗

Generalized minimum shift-keying modulation techniques

The simultaneous data demodulation and phase tracking of an MSK signal using the Viterbi algorithm is described and two variations of MSK modulation are studied. The MSK with overlay is a dual rate modulation technique where low-and high-rate data are superimposed on an MSK signal. Here the demodulator uses the Viterbi algorithm to estimate both the low-and high-rate data simultaneously. The MSK with pseudorandom sequence spreading combats intentional or unintentional jamming. A simplified receiver for these spread spectrum MSK signals is found, which takes into consideration the effect of random phase perturbations. The performance of these demodulators is evaluated using transfer function bounds for the bit error probability. It is shown that with a reasonable short overlay period, at a relatively high signal-to-noise ratio (13 dB), there is a small (0.7 dB) loss of performance. For demodulation of the spread spectrum MSK signal, a simplified receiver is derived, and its performance in the presence of continuous jamming is evaluated.

Sadr, Ramin↗

Measurement-based performance evaluation technique for high-performance computers

A measurement-based performance evaluation technique has been used to characterize the OS performance of Cedar, a hierarchical shared-memory multiprocessor system. Thirteen OS performance meters were used to capture the operating system activities for compute-bound workloads. Three representative applications from the Perfect Benchmark Suite were used to measure the OS performance in a dedicated system and in multiprogrammed workloads. It was found that 13-23 percent of the total execution time on a dedicated system was spent in executing OS-related activities. Under multiprogramming, 12-14 percent of the total execution time was used by the OS. The impact of multiprogramming on the operating system performance meters was also measured.

Sharma, S.↗

High-Burnup BWR LOCA Burst Analysis Using High-Fidelity Multiphysics Simulations

The US nuclear industry is looking to improve on the operating economics of the current fleet of light-water reactors (LWRs). One way of achieving this is by operating fuel to higher burnup. In pressurized water reactors (PWRs), relaxing the current burnup limit will allow for cycle length extensions and power uprates; in boiling water reactors (BWRs) it may allow for improved fuel utilization and reduced feed assemblies, as well as more efficient power uprates and increased capacity factors that will support the Administration’s Executive Order to facilitate 5 GW of power uprates at existing nuclear facilities. However, one of the key limitations to operating fuel to higher burnup is the risk of fuel fragmentation, relocation, and dispersal (FFRD). Recognizing the high interest in extending burnup limits, the US Nuclear Regulatory Commission (NRC) has issued Draft Regulatory Guide DG-1434, which defines an approach that would be acceptable to the NRC for addressing FFRD risk. The approach defined will require better understanding of the phenomena leading to FFRD as well as best-estimate simulation methods to understand FFRD risk in high-burnup cores. The Nuclear Energy Advanced Modeling and Simulation program is supporting the FFRD industry challenge problem through development of state-of-the-art, high-fidelity modeling and simulation LWR analysis capabilities; namely, the BISON fuel performance code and the VERA core simulator software. These tools, along with the US NRC TRACE system analysis code, have been utilized for analysis of FFRD risk in both PWR and BWR cores in recent years. The work documented in this report addresses the lack of high-fidelity research for BWRs and builds on a previous activity where the framework has been applied to Cycles 16 through 18 of Limerick Unit 1, a BWR/4, with introduction of 8 high-burnup lead use assemblies (HBLUAs) that were representative of the 8 HBLUAs loaded into Limerick Unit 2 in 2021. VERA was used in this previous activity to model rod-by-rod depletion in these cycles, and its solution was used to initialize a TRACE simulation of a large-break loss-of-coolant accident (LBLOCA) at the end of Cycle 18. In the work documented in this report, the TRACE model was improved by refining the core mesh and utilizing a new feature that allows for capturing the full 3D VERA power distribution in the model. This allows for a more detailed solution for setting BISON boundary conditions. Furthermore, the solutions from VERA and TRACE were used to set up and perform BISON simulations of about 1,000 rods sampled from the core, including all burnup levels. Utilizing two cladding burst models, it was shown that no fuel rods were predicted to burst during the postulated LBLOCA transient. Additionally, a sensitivity study was performed by artificially increasing linear heat rate during the postulated LBLOCA to identify parameters that correlate with rod burst susceptibility. Burnup, fission gas release, and hoop strain were all found to be positively correlated with rod burst susceptibility. Small-break loss-of-coolant accident (SBLOCA) analyses were also performed; these analyses predicted cladding temperature increases that were bounded by the LBLOCA cladding temperatures for all small break sizes studied for this plant. However, future refinements to the plant response assumptions during the SBLOCA could impact the predicted cladding response. Finally, a benchmark study was performed between CTF and TRACE for LOCA conditions to better qualify CTF for BWR LOCA modeling.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modulating Operational Conditions to Mitigate Deactivation in Formate Dehydrogenation on Pd Phases

In heterogeneous catalysis, poisoning by surface-bound intermediates poses a major barrier to sustained catalyst performance in (de)hydrogenation reactions. Formate/bicarbonate systems, as liquid organic hydrogen carriers (LOHCs), offer a CO 2 -integrated, low-temperature pathway for hydrogen storage and release, making them attractive for circular energy applications. However, their lower hydrogen density and susceptibility to catalyst deactivation limit their competitiveness compared to conventional LOHCs like methylcyclohexane. Here, this study investigates the mechanistic origins of formate (HCOO – ) dehydrogenation and associated deactivation on Pd interfaces. Using density functional theory (DFT) simulations, we show that under thermocatalytic conditions, strongly bound formate accumulates on the catalyst surface (Pd(111)), blocking active sites, raising activation barriers, and leading to progressive performance loss. Because formate adsorption involves charge transfer, we exploit its sensitivity to electronic structure by modulating the electrochemical potential of the catalyst. Our results reveal that hydrogen transfer from water and formate exhibits opposing potential dependencies, providing insights into the opposing driving forces behind both catalytic activity and poisoning. To further probe this phenomenon, we examine electrochemically induced phase transitions in Pd, focusing on PdO(100) and PdH(110), which are stable under oxidizing and reducing potentials, respectively, and demonstrate enhanced dehydrogenation activity between −0.4 and 0.2 V vs standard hydrogen electrode (SHE). Complementary thermal treatments help decouple kinetic and thermodynamic contributions to intermediate binding. These findings underscore the critical role of the catalyst phase and external stimuli in dictating poison-active site interactions and highlight phase engineering as a promising strategy to mitigate deactivation. This work offers mechanistic insights and design principles for developing more resilient and efficient catalysts for LOHC applications under realistic operating conditions.

Pd phase↗

Unsupervised Anomaly Detection in High-Dimensional Flight Data Using Convolutional Variational Auto-Encoder

The modern National Airspace System (NAS) is an extremely safe system. The industry has experienced a steady decrease in fatalities over the years. This can be contributed to both improved flight critical systems with redundant hardware and software protections as well as an increased focus on active monitoring and response to real time and historically identified vulnerabilities by implementing more resilient procedures and protocols. The main practice for identifying vulnerabilities in operations leverages domain expertise using knowledge about how the system should behave with the expected tolerances to known safety margins. This approach works well when the system has a well-defined operating condition. However, the operations in the NAS can be highly complex with various nuances that render it difficult to clearly pre-define all known safety vulnerabilities. With the advancement of data science and machine learning techniques, the potential to automatically identify emerging vulnerabilities in the observed operations has become more practical in recent years. The state-of-the-art anomaly detection approaches in aerospace data usually rely on supervised or semi-supervised learning. However, in many real-world problems such as flight safety creating labels for the data requires huge amount of efforts and is largely expensive. As a result, in this article, we develop a Convolutional Variational Auto-Encoder (CVAE), an unsupervised learning approach for anomaly detection in high-dimensional heterogeneous time-series data. We validate performance of CVAE compared to the state-of-the-art supervised learning approach (as an upper bound) as well as an supervised clustering based on K-Means (as a lower bound) on Yahoo!'s benchmark time series anomaly detection data. Finally, we showcase performance of CVAE on a case study of identifying anomalies in the first 60 seconds of commercial flights' take-offs using Flight Operational Quality Assurance (FOQA) data.

Milad Memarzadeh↗

Viscosity bounds in liquids with different structure and bonding types

Recently, it was realized that liquid viscosity has a lower bound which is nearly constant for all liquids and is governed by fundamental physical constants. This was supported by experimental data in noble and molecular liquids. Here, we perform large-scale molecular dynamics simulations to ascertain this bound in two other important liquid types: the ionic molten salt system LiF and metallic Pb. We find that these ionic and metallic systems similarly have lower viscosity bounds corresponding to the minimum of kinematic viscosity of ∼ 10 − 7 m 2 / s . We show that this agrees with experimental data in other systems with different structures and bonding types, including noble, molecular, metallic, and covalent liquids. This expands the universality of viscosity bounds into the main system types known. Published by the American Physical Society 2024

Materials Science↗

Multilevel Conditional Disturbance Rejection Control for Satellite Attitude Tracking

Recently, the conditional disturbance rejection controller (CDRC) was proposed to improve control performance by leveraging disturbances that have beneficial effects on the system. However, it only considers disturbances acting on the state variable directly influenced by them. Although fast convergence of this state can be achieved with the CDRC, it may unintentionally affect the convergence of the output (i.e., the primary state). Here, in this article, a multilevel CDRC is proposed to enhance satellite attitude control performance by accounting for the effect of disturbances on both attitude (output) and angular velocity. The extended state observer is employed to estimate the lumped disturbance, including the modeling errors and external disturbances. Then, a backstepping-based controller with the multilevel disturbance rejection law (ML-DRL) is designed for attitude tracking. The ML-DRL is developed to improve the control performance by using a disturbance with a damping effect on both attitude and velocity. Faster convergence of attitude and velocity can be achieved by conditionally compensating for the disturbance. The stability of the proposed control method is analyzed by demonstrating that the errors are bounded as time tends to infinity. The attitude control performance of the proposed method is evaluated through numerical examples conducted using the MATLAB/Simulink Multibody tool.

Active disturbance rejection control (ADRC)↗

Ultra-selective CANAL Polymers for Hydrogen-based Membrane Separations after Long-Term Aging

Hydrogen is a critically important molecule in the chemicals and energy industries, driving the need for efficient purification technologies such as membrane-based separations. However, polymer membranes often suffer from physical aging, leading to decreased gas permeability over time. This study leverages the unique aging behavior of contorted microporous polymers, synthesized via catalytic arene-norbornene annulation (CANAL) polymerization, to enhance molecular sieving for H 2 separations. While prior studies demonstrated a 1000% increase in H 2 /CH 4 selectivity with minimal permeability loss over 150 days, we extend this investigation to hyperaged (∼1 year) CANAL polymers and evaluate their performance under various conditions of industrial relevance. We report a remarkable 6100% increase in H 2 /CH 4 selectivity and a 2400% improvement in H 2 /N 2 selectivity, with only a 55% decline in H 2 permeability. These membranes exhibit excellent long-term stability in binary and ternary gas mixtures and at elevated temperatures. Additionally, extended aging enhances H 2 /CO 2 selectivity beyond the 2008 upper bound due to improved size-sieving. High-temperature permeation experiments and grand canonical Monte Carlo simulations reveal that H 2 permeability increases from 570 to 3500 barrer as the temperature rises from 35 °C to 190 °C, while H 2 /CO 2 selectivity declines from 14 to 3 due to the higher diffusion activation energy of CO 2 . Despite this tradeoff, hyperaged CANAL membranes maintain performance beyond the 200 °C upper bound, having selectivity–permeability performance comparable to many state-of-the-art membranes for H 2 /CO 2 separations. As a result, this study highlights the robustness and industrial viability of ultra-selective CANAL polymers for hydrogen purification, contributing to advancements in clean energy and sustainable separation technologies.

36 MATERIALS SCIENCE↗

Coefficient-to-Basis Network: a fine-tunable operator learning framework for inverse problems with adaptive discretizations and theoretical guarantees

We propose a Coefficient-to-Basis Network (C2BNet), a novel framework for solving inverse problems within the operator learning paradigm. C2BNet efficiently adapts to different discretizations through fine-tuning, using a pre-trained model to significantly reduce computational cost while maintaining high accuracy. Unlike traditional approaches that require retraining from scratch for new discretizations, our method enables seamless adaptation without sacrificing predictive performance. Furthermore, we establish theoretical approximation and generalization error bounds for C2BNet by exploiting low-dimensional structures in the underlying datasets. Our analysis demonstrates that C2BNet adapts to low-dimensional structures without relying on explicit encoding mechanisms, highlighting its robustness and efficiency. To validate our theoretical findings, we conducted extensive numerical experiments that showcase the superior performance of C2BNet on several inverse problems. The results confirm that C2BNet effectively balances computational efficiency and accuracy, making it a promising tool to solve inverse problems in scientific computing and engineering applications.

97 MATHEMATICS AND COMPUTING↗

Testing of Crystalline Silicotitanate to Support Tank-Side Cesium Removal System Operations - 20458

The direct feed of waste from the Hanford tank farms to the Low-Activity Waste Facility at the Hanford Waste Treatment and Immobilization Plant requires an intermediate treatment step that prepares the waste for vitrification. Washington River Protection Solutions (WRPS) selected a near-tank treatment system known as the Tank-Side Cesium Removal (TSCR) system to perform the required intermediate treatment functions. The approach in the TSCR system is to filter waste supernatant with a sintered metal dead-end filter and then use a series of ion exchange columns to remove cesium; this system has several similarities to the Tank Closure Cesium Removal system that has been deployed on the Savannah River Site. The ion exchange media proposed for use is crystalline silicotitanate (CST), which is a non-elutable media with a high affinity for cesium. Because the media is non-elutable, loaded columns will be blown down with compressed air, moved into interim storage, and replaced with new columns when cesium capacity is reached. The assumed extent and rate of drying that could be achieved in the TSCR column geometry lacked confirmation by experimental data. In addition, once the columns are loaded with cesium, they generate flammable gases (primarily hydrogen) via radiolysis acting on any resident liquids, i.e., moisture, remaining in the media bed. An assessment of available information on CST concluded that gas generation data that bounds expected operational conditions were needed to support the TSCR system safety basis and planned operations. Working with WRPS, Pacific Northwest National Laboratory (PNNL) designed and conducted testing with CST media to address the need for (a) representative in-column drying data, and (b) bounding flammable gas generation data. Drying testing was performed using a full-height column with a diameter of approximately 2 inches with injected air at temperatures of 18 deg. C and 30 deg. C. Gas generation testing was conducted in an engineered bunker that allowed simultaneous irradiation of up to eight samples at a time. These two experimental approaches used at PNNL for the CST testing are summarized and the major outcomes are presented. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Channel assignments and array gain bounds for the Ka-band array feed compensation system

The performance of a real-time digital combining system for use with array feeds was considered previously. The purpose of the combining operation is to recover signal to noise ratio (SNR) losses due to antenna deformations and atmospheric effects. Previously, arbitrary signal powers and noise variances were assumed, but no attempt was made to match the receiver channels to the available signal powers. It is shown that for any signal power and noise variance distribution, a best channel assignment exists that maximizes the combined SNR in the limit of vanishingly small combining losses. This limit can be approached in practice by observing sufficiently many samples. Specific signal power and noise variance distributions are considered, and it is shown that even relatively noisy channels can be used effectively to recover SNR losses resulting from signals diverted out of a high-quality channel by antenna deformations.

Vilnrotter, V. A.↗

Deep Space navigation for the BioSentinel spacecraft science orbit

BioSentinel is an astrobiology small spacecraft mission. The payload consists of two parts, the first has optical and microfluidics sensors, and the second is a Linear Energy Transfer spectrometer that has the objective to measure deep space radiation from events such as coronal mass ejections. The goal of the mission is to observe potential DNA damage due to the radiation in heliocentric space on the living organism Saccharomyces cerevisiae, which is a budding yeast. Two types of this living organism are included in the payload. The first is a natural type that is more radiation tolerant, while the second is a mutant strain that has a deficiency in a gene that allows DNA repair once damage occurs. The impact caused by the radiation on the DNA is compared to an identical sample aboard the International Space Station, as well as another identical sample at a laboratory on the ground. The BioSentinel mission consists of a 6U CubeSat currently ,as of January 2024, active in heliocentric orbit. The spacecraft was launched aboard the first SLS flight as part of the Artemis-I campaign in November 2022. After successful deployment from the launch vehicle, it performed a lunar flyby with an altitude of 406 km. The delta-V imparted by the flyby provided the necessary energy to achieve a heliocentric orbit, in an Earth-trailing pattern. The navigation analysis consisted of a Kalman-filter that utilized data from the Deep Space Network and the ESA Estrack network. All those antennas were needed since the Artemis-1 campaign included the deployment of several other cubesats, therefore the scheduling process required more antenna assets than usual due to simultaneous demands from various missions. The processed tracking data was later also refined with a smoother in order to obtain a more accurate solution. The type of tracking data included TCP, Sequential Range, Doppler and Range formats. The solar radiation pressure coefficient, as well as the delta-V from the deployment and the flyby were modeled to obtain suitable solutions that could decrease the position and velocity uncertainties at several steps along the mission concept of operations. The final product each time resulted in updated ephemeris files that were used by the mission and the antenna networks as the mission progressed. Once in the final science orbit, the utilized antennas are only from the DSN network and the data format is bounded to just TCP. Regular orbit determination is performed, every two weeks. The spacecraft is in a nominal well-known orbit, performing regular operations. This paper includes an analysis of the final science orbit, the techniques and procedures utilized to perform orbit determination and a description of the overall navigation campaign produced during the mission and, more specifically, during the final science operations in Deep Space.

BioSentinel↗

Bounds of the bit error probability of a linear cyclic code over GF(2 exp l) and its extended code

An upper bound on the bit-error probability (BEP) of a linear cyclic code over GF(2 exp l) with hard-decision (HD) maximum-likelihood (ML) decoding on memoryless symmetric channels is derived. Performance results are presented for Reed-Solomon codes on GF(32), GF(64), and GF(128). Also, a union upper bound on the BEP of a linear cyclic code with either HD or soft-decision (SD) ML decoding is developed, as well as the corresponding bounds for the extended code of a linear cyclic code. Using these bounds, which are tight at low bit error rate, the performance advantage of SD and HD ML over bounded-distance decoding is established.

Cheng, Unjeng↗