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Towards a Circular Economy for PET Bottles in the U.S. - 4P Framework

The United States generates the most plastic waste of any country. Along with that GHG emissions from the global plastic economy are expected to increase to 15% of the global carbon budget by 2050. It is imperative that plastic recycling is made a reality to reduce both plastic pollution in the environment and GHG emissions. A portfolio of end-of-life strategies must be implemented to minimize environmental impacts and retain valuable plastic material, but it is challenging to compare options that generate products with different utility and lifetime. Plastic use reduction, reuse and recycling are thus increasingly important, but making informed policy and research decisions within this space can be challenging given the diverse range of available solutions. The novel analysis framework, Plastic Parallel Pathways Platform (4P) has been equipped with consequential life cycle assessment, techno-economic analysis, and a plastic circularity indicator to estimate the greenhouse gas (GHG) emissions, circularity, and cost of polyethylene terephthalate (PET) down-cycling to lower-quality resin, closed-loop recycling to food-grade PET bottles, up-cycling to fiber-reinforced plastic (FRP), and conversion to non-plastic products (electricity, oil) on a United States economy-wide basis. Integrating system dynamics into this robust plastics model that already incorporates techno-economics, circularity, and environmental impacts will enable identification of key bottlenecks between manufacturers, waste sorters, and reclaimers that currently prevent rapid decarbonization of the plastics economy. System dynamics (SD) explore the evolution of activities and technologies based on changed macro parameters such as plastic demand and supply, market shifts, and cross-sectoral interactions. This project particularly aims to explore the interplay between, waste collection, plastic waste sorting, recycling, and manufacturing, as well as the effect of plastic bale quality and plastic reuse initiatives on the surrounding process stages. This functionality will facilitate combinatory analysis in which a portfolio of end-of-life pathways are assessed simultaneously, with the exact makeup of that portfolio affected by parameters such as technology scales, resource constraints, and waste mitigation efforts. Integrating SD with the 4P framework enables analyzing the effect of increased revenue and reinvestment into improving process efficiencies, sorting and collection quantities. Through that, market effects of increased recycled resin availability can be studied for the plastics systems model for the US. The results will help identify technical or economic bottlenecks that currently limit efforts to decarbonize the U.S. plastics economy.

circular economy↗

Model Development and Experimental Validation of the Fusible Heat Sink Design for Exploration Vehicles

The Fusible Heat Sink is a novel vehicle heat rejection technology which combines a flow through radiator with a phase change material. The combined technologies create a multi-function device able to shield crew members against Solar Particle Events (SPE), reduce radiator extent by permitting sizing to the average vehicle heat load rather than to the peak vehicle heat load, and to substantially absorb heat load excursions from the average while constantly maintaining thermal control system setpoints. This multi-function technology provides great flexibility for mission planning, making it possible to operate a vehicle in hot or cold environments and under high or low heat load conditions for extended periods of time. This paper describes the modeling and experimental validation of the Fusible Heat Sink technology. The model developed was intended to meet the radiation and heat rejection requirements of a nominal MMSEV mission. Development parameters and results, including sizing and model performance will be discussed. From this flight-sized model, a scaled test-article design was modeled, designed, and fabricated for experimental validation of the technology at Johnson Space Center thermal vacuum chamber facilities. Testing showed performance comparable to the model at nominal loads and the capability to maintain heat loads substantially greater than nominal for extended periods of time.

Cognata, Thomas J.↗

Exploring laser-material interactions of zirconium carbide under additive manufacturing conditions

Zirconium carbide (ZrC) is an ultra-high temperature ceramic with a melting temperature above 3000°C and a broad range of high temperature applications. Given the high melting and sintering temperatures of pure ZrC, producing near-net shape and fully dense parts remains challenging with conventional techniques. In this study, we investigate the fundamental laser-material interactions of ZrC under laser powder bed fusion (LPBF) additive manufacturing (AM) conditions. Normalized enthalpy, a scaling law term that is used in welding and AM literature for detailing laser-material interactions in metallic alloys, was calculated to determine the predictive capabilities of melt pool features in ZrC. Further, the melt pool quality of laser irradiated ZrC was used to compare LPBF relevant laser parameter combinations of laser power, scan speed, and beam diameter. Laser build parameters that resulted in desirable melt pool morphologies were applied to the fabrication of ZrC coupons using LPBF AM. A custom LPBF system was used to determine hatch spacing and layer height parameters that resulted in a fabricated sample with a density of 85% as measured by Archimedes and a Vicker's microhardness of 20.9 ± 1.9 GPa. This investigation reveals the laser-material interactions of ZrC under AM relevant conditions and is the first step towards LPBF fabrication of ZrC parts.

36 MATERIALS SCIENCE↗

Machine-Learning Analysis of Radiative Decays to Dark Matter at the LHC

The search for weakly interacting matter particles (WIMPs) is one of the main objectives of the High Luminosity Large Hadron Collider (HL-LHC). In this work we use Machine-Learning (ML) techniques to explore WIMP radiative decays into a Dark Matter (DM) candidate in a supersymmetric framework. The minimal supersymmetric WIMP sector includes the lightest neutralino that can provide the observed DM relic density through its co-annihilation with the second lightest neutralino and lightest chargino. Moreover, the direct DM detection cross section rates fulfill current experimental bounds and provide discovery targets for the same region of model parameters in which the radiative decay of the second lightest neutralino into a photon and the lightest neutralino is enhanced. This strongly motivates the search for radiatively decaying neutralinos which, however, suffers from strong backgrounds. We investigate the LHC reach in the search for these radiatively decaying particles by means of cut-based and ML methods and estimate its discovery potential in this well-motivated, new physics scenario. We demonstrate that using ML techniques would enable access to most of the parameter space unexplored by other searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Model Development and Experimental Validation of the Fusible Heat Sink Design for Exploration Vehicles

The Fusible Heat Sink is a novel vehicle heat rejection technology which combines a flow through radiator with a phase change material. The combined technologies create a multi-function device able to shield crew members against Solar Particle Events (SPE), reduce radiator extent by permitting sizing to the average vehicle heat load rather than to the peak vehicle heat load, and to substantially absorb heat load excursions from the average while constantly maintaining thermal control system setpoints. This multi-function technology provides great flexibility for mission planning, making it possible to operate a vehicle in hot or cold environments and under high or low heat load conditions for extended periods of time. This paper describes the model development and experimental validation of the Fusible Heat Sink technology. The model developed was intended to meet the radiation and heat rejection requirements of a nominal MMSEV mission. Development parameters and results, including sizing and model performance will be discussed. From this flight-sized model, a scaled test-article design was modeled, designed, and fabricated for experimental validation of the technology at Johnson Space Center thermal vacuum chamber facilities. Testing showed performance comparable to the model at nominal loads and the capability to maintain heat loads substantially greater than nominal for extended periods of time.

Cognata, Thomas J.↗

Flash Cracking Reactor for Waste Plastic Processing

Conversion of waste plastic to energy is a growing problem that is especially acute in space exploration applications. Moreover, utilization of heavy hydrocarbon resources (wastes, waxes, etc.) as fuels and chemicals will be a growing need in the future. Existing technologies require a trade-off between product selectivity and feedstock conversion. The objective of this work was to maintain high plastic-to-fuel conversion without sacrificing the liquid yield. The developed technology accomplishes this goal with a combined understanding of thermodynamics, reaction rates, and mass transport to achieve high feed conversion without sacrificing product selectivity. The innovation requires a reaction vessel, hydrocarbon feed, gas feed, and pressure and temperature control equipment. Depending on the feedstock and desired product distribution, catalyst can be added. The reactor is heated to the desired tempera ture, pressurized to the desired pressure, and subject to a sweep flow at the optimized superficial velocity. Software developed under this project can be used to determine optimal values for these parameters. Product is vaporized, transferred to a receiver, and cooled to a liquid - a form suitable for long-term storage as a fuel or chemical. An important NASA application is the use of solar energy to convert waste plastic into a form that can be utilized during periods of low solar energy flux. Unlike previous work in this field, this innovation uses thermodynamic, mass transport, and reaction parameters to tune product distribution of pyrolysis cracking. Previous work in this field has used some of these variables, but never all in conjunction for process optimization. This method is useful for municipal waste incinerator operators and gas-to-liquids companies.

Timko, Michael T.↗

Electrical Cable Design for Urban Air Mobility Aircraft

Urban Air Mobility (UAM) describes a new type of aviation focused on efficient flight within urban areas for moving people and goods. There are many different configurations of UAM vehicles, but they generally use an electric motor driving a propeller or ducted fan powered by batteries or a hybrid electric power generation system. Transmission cables are used to move energy from the storage or generation system to the electric motors. Though terrestrial power transmission cables are well established technology, aviation applications bring a whole host of new design challenges that are not typical considerations in terrestrial applications. Aircraft power transmission cable designs must compromise between resistance-per-length, weight-per-length, volume constraints, and other essential qualities. In this paper we use a multidisciplinary design optimization to explore the sensitivity of these qualities to a representative tiltwing turboelectric UAM aircraft concept. This is performed by coupling propulsion and thermal models for a given mission criteria. Results presented indicate that decreasing cable weight at the expense of increasing cable volume or cooling demand is effective at minimizing maximum takeoff weight (MTO). These findings indicate that subsystem designers should update their modeling approach in order to contribute to system-level optimality for highly-coupled novel aircraft. Mobility (UAM) vehicles have the potential to change urban and intra-urban transport in new and interesting ways. In a series of two papers Johnson et al.1 and Silva et al.2 presented four reference vehicle configurations that could service different niches in the UAM aviation category. Of those, this paper focuses on the Vertical Take-off and Landing (VTOL) tiltwing configuration shown in Figure 1. This configuration uses a turboelectric power system, feeding power from a turbo-generator through a system of transmission cables to four motors spinning large propellers on the wings. Previous work on electric cable subsystems leaves much yet to be explored, especially in the realm of subsystem coupling. Several aircraft optimization studies1, 3, 4 only considered aircraft electrical cable weight and ignored thermal effects. Electric and hybrid-electric aircraft studies by Mueller et al.5 and Hoelzen et al.6 selected a cable material but did not investigate alternative materials. Advanced cable materials have been examined by a number of authors: Alvarenga7 examined carbon nanotube (CNT) conductors for low-power applications. De Groh8, 9 examined CNT conductors for motor winding applications. Behabtu et al.,10 and Zhao et al.11 examined CNT conductors for a general applications. There were some studies that examined the thermal effects of cables but they did not allow the cable material to change; El-Kady12 optimized ground-cable insulation and cooling subject constraints. Vratny13 selected cable material based on vehicle power demand, and required resulting cable heat to be dissipated by the Thermal Management System (TMS). None of these previous studies allowed for the selection of the cable material based on a system level optimization goal. Instead, they focused on sub-system optimality such as minimum weight, which comes at the expense of incurring additional costs for other subsystems. Dama14 selected overhead transmission line materials using a weighting function and thermal constraints. However, that work was not coupled with any aircraft subsystems like a TMS. The traditional aircraft design approach, which relies on assembling groups of optimal subsystems, breaks down when considering novel aircraft concepts like the tiltwing vehicle. In a large part, this is because novel concepts have a much higher degree of interaction or coupling between subsystems. For example, when a cable creates heat, this heat needs to be dissipated by the TMS, which needs power supplied by the turbine, and delivering the power creates more heat. The cable, the TMS, and the turbine are all coupled. A change to one subsystem will affect all the other subsystems, much to the consternation of subsystem design experts. Multidisciplinary optimization is the design approach that can address these challenges. However, to fully take advantage of this, we must change the way we think about subsystem design. Specifically, we must move away from point design, and focus on creating solution spaces. The work presented in this paper uses the multidisciplinary optimization approach with aircraft level models to study the system-level sensitivity of cable traits: weight-per-length and resistance-per-length. Additionally, we examined the effects of vehicle imposed volume constraints on these traits. This is useful for three purposes: (1) to demonstrate a framework that can perform a coupled analysis between the aircraft thermal and propulsion systems, (2) to provide a method by which future cable designs can be evaluated against each other given a system-level design goal, (3) to provide insight into what cable properties may be promising for future research. This last element is explored given the caveat that the models contained in this analysis do not represent high-fidelity systems. Thus, while we can demonstrate coupling in between systems, the exact system-level sensitivity to a given parameter may change if a subsystem model or the assumptions governing that model change. The organization of this paper is as follows, in Sec II we outline a method to combine the VTOL vehicle design and cable information in order to produce cables sensitivity studies. Results analysis and discussion are contained in Sec III. Conclusions are presented in Sec IV.

Aretskin-Hariton, Eliot D.↗

Effects of Optimisation Parameters on Data-Driven Magnetofrictional Modelling of Active Regions

Context . The solar magnetic field plays an essential role in the formation, evolution, and dynamics of large-scale eruptive structures in the corona. The estimation of the coronal magnetic field, the ultimate driver of space weather, particularly in the ‘low’ and ‘middle’ corona, is presently limited due to practical difficulties. Data-driven time-dependent magnetofrictional modelling (TMFM) of active region magnetic fields has been proven to be a useful tool to study the corona. The input to the model is the photospheric electric field that is inverted from a time series of the photospheric magnetic field. Constraining the complete electric field, that is, including the non-inductive component, is critical for capturing the eruption dynamics. We present a detailed study of the effects of optimisation of the non-inductive electric field on the TMFM of AR 12473. Aims . We aim to study the effects of varying the non-inductive electric field on the data-driven coronal simulations, for two alternative parametrisations. By varying parameters controlling the strength of the non-inductive electric field, we wish to explore the changes in flux rope formation and their early evolution and other parameters, for instance, axial flux and magnetic field magnitude. Methods . We used the high temporal and spatial resolution cadence vector magnetograms from the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). The non-inductive electric field component in the photosphere is critical for energising and introducing twist to the coronal magnetic field, thereby allowing unstable configurations to be formed. We estimated this component using an approach based on optimising the injection of magnetic energy. Results . Our data show that flux ropes are formed in all of the simulations except for those with the lower values of these optimised parameters. However, the flux rope formation, evolution and eruption time varies depending on the values of the optimisation parameters. The flux rope is formed and has overall similar evolution and properties with a large range of non-inductive electric fields needed to determine the non-inductive electric field component that is critical for energising and introducing twist to the coronal magnetic field. Conclusions . This study shows that irrespective of non-inductive electric field values, flux ropes are formed and erupted, which indicates that data-driven TMFM can be used to estimate flux rope properties early in their evolution without needing to employ a lengthy optimisation process.

A. Kumari↗

Lunar Explorer Instrument for space biology Applications (LEIA): An overview of planned science concept of operations

Radiation and reduced gravity pose biological risks to crewed deep space exploration. To better understand deep space radiation biology, the LEIA mission will measure charged particles and fast neutrons as well as yeast growth, metabolic rate, and bioengineered production of carotenoids at the lunar surface. LEIA will be delivered to the south polar region of the Moon by the Commercial Lunar Payload Services (CLPS) program. The LEIA science concept of operations was developed to isolate radiation and partial gravity from other environmental conditions experienced by the payload. Due to CLPS integration requirements, there will be at least eight months from loading yeast into the payload until activation on the lunar surface. Replicate yeast strains will be loaded in a randomized complete block design to minimize batch differences in desiccation tolerance and positional effects in the microfluidics culture system. Temperature and relative humidity will be controlled throughout integration and flight to maintain yeast viability and to enable measurement of yeast growth parameters within the lunar surface operations timeframe, with the ground control matching environmental conditions where possible. LEIA is co-manifested with the European Space Agency’s PROSPECT mission, which will be operating a drill during yeast growth. Vibration translated through the lunar lander will be mitigated and quantified to account for potential impacts on LEIA optical measurements and yeast growth rate. Total space radiation dose, including the transit exposure from Earth to the Moon, will be measured to obtain more accurate charged particle and fast neutron dose rates on the lunar surface. These radiation data will also yield ground truth radiation dose experienced by the yeast during the mission. Quantifying these environmental factors impacting the LEIA payload will allow more accurate ground control experiments to better isolate the biological responses to radiation and reduced gravity at the lunar surface.

Lunar Surface Mission↗

Space Environment (Natural and Induced)

Considerable effort and improvement have been made in the study of ionizing radiation exposure occurring in various regions of space. Satellites and spacecrafts equipped with innovative instruments are continually refining particle data and providing more accurate information on the ionizing radiation environment. The major problem in accurate spectral definition of ionizing radiation appears to be the detailed energy spectra, especially at high energies, which is important parameter for accurate radiation risk assessment. Magnitude of risks posed by exposure to radiation in future space missions is subject to the accuracies of predictive forecast of event size of SPE, GCR environment, geomagnetic fields, and atmospheric radiation environment. Although heavy ion fragmentations and interactions are adequately resolved through laboratory study and model development, improvements in fragmentation cross sections for the light nuclei produced from HZE nuclei and their laboratory validation are still required to achieve the principal goal of planetary GCR simulation at a critical exposure site. More accurate prediction procedure for ionizing radiation environment can be made with a better understanding of the solar and space physics, fulfillment of required measurements for nuclear/atomic processes, and their validation and verification with spaceflights and heavy ion accelerators experiments. It is certainly true that the continued advancements in solar and space physics combining with physical measurements will strengthen the confidence of future manned exploration of solar system. Advancements in radiobiology will surely give the meaningful radiation hazard assessments for short and long term effects, by which appropriate and effective mitigation measures can be placed to ensure that humans safely live and work in the space, anywhere, anytime.

Kim, Myung-Hee Y.↗

Integrated Extravehicular Activity Human Research Plan: 2017

Multiple organizations within NASA as well as industry and academia fund and participate in research related to extravehicular activity (EVA). In October 2015, representatives of the EVA Office, the Crew and Thermal Systems Division (CTSD), and the Human Research Program (HRP) at NASA Johnson Space Center agreed on a formal framework to improve multi-year coordination and collaboration in EVA research. At the core of the framework is an Integrated EVA Human Research Plan and a process by which it will be annually reviewed and updated. The over-arching objective of the collaborative framework is to conduct multi-disciplinary cost-effective research that will enable humans to perform EVAs safely, effectively, comfortably, and efficiently, as needed to enable and enhance human space exploration missions. Research activities must be defined, prioritized, planned and executed to comprehensively address the right questions, avoid duplication, leverage other complementary activities where possible, and ultimately provide actionable evidence-based results in time to inform subsequent tests, developments and/or research activities. Representation of all appropriate stakeholders in the definition, prioritization, planning and execution of research activities is essential to accomplishing the over-arching objective. A formal review of the Integrated EVA Human Research Plan will be conducted annually. Coordination with stakeholders outside of the EVA Office, CTSD, and HRP is already in effect on a study-by-study basis; closer coordination on multi-year planning with other EVA stakeholders including academia is being actively pursued. Details of the preliminary Integrated EVA Human Research Plan are presented including description of ongoing and planned research activities in the areas of: physiological and performance capabilities; suit design parameters; EVA human health and performance modeling; EVA tasks and concepts of operations; EVA informatics; human-suit sensors; suit sizing and fit; and EVA injury risk and mitigation. This paper represents the 2017 update to the Integrated EVA Human Research Plan.

Abercromby, Andrew↗

Uncertainty quantification for Bayesian active learning in rupture life prediction of ferritic steels

Abstract Three probabilistic methodologies are developed for predicting the long-term creep rupture life of 9–12 wt%Cr ferritic-martensitic steels using their chemical and processing parameters. The framework developed in this research strives to simultaneously make efficient inference along with associated risk, i.e., the uncertainty of estimation. The study highlights the limitations of applying probabilistic machine learning to model creep life and provides suggestions as to how this might be alleviated to make an efficient and accurate model with the evaluation of epistemic uncertainty of each prediction. Based on extensive experimentation, Gaussian Process Regression yielded more accurate inference ( $$Pearson\;correlation\;coefficent> 0.95$$ P e a r s o n c o r r e l a t i o n c o e f f i c e n t > 0.95 for the holdout test set) in addition to meaningful uncertainty estimate (i.e., coverage ranges from 94 to 98% for the test set) as compared to quantile regression and natural gradient boosting algorithm. Furthermore, the possibility of an active learning framework to iteratively explore the material space intelligently was demonstrated by simulating the experimental data collection process. This framework can be subsequently deployed to improve model performance or to explore new alloy domains with minimal experimental effort.

20 FOSSIL-FUELED POWER PLANTS↗

Gravitational waves and galaxies cross-correlations: a forecast on GW biases for future detectors

ABSTRACT Gravitational waves (GWs) have rapidly become important cosmological probes since their first detection in 2015. As the number of detected events continues to rise, upcoming instruments like Einstein Telescope (ET) and Cosmic Explorer (CE) will observe millions of compact binary mergers. These detections, coupled with galaxy surveys by instruments such as the Dark Spectroscopic Energy Instrument (DESI), Euclid, and the Vera Rubin Observatory, will provide unique information on the large-scale structure of the universe by cross-correlating GWs with the distribution of galaxies hosting them. In this paper, we focus on how cross-correlations constrain the clustering bias of GWs emitted by the coalescence of binary black holes (BBHs). This parameter links BBHs to the underlying dark matter distribution, hence informing us how they populate galaxies. Using a multitracer approach, we forecast the precision of these measurements under different survey combinations. Our results indicate that current GW detectors will have limited precision, with measurement errors as high as $\displaystyle \sim 50~{{\ \rm per\ cent}}$. However, third-generation detectors like ET, when cross-correlated with Legacy Survey of Space and Time (LSST) data, can improve clustering bias measurements to within 2.5 per cent. Furthermore, we demonstrate that these cross-correlations can enable a per cent-level measurement of the magnification lensing effect on GWs. Despite this, there is a degeneracy between magnification and evolution biases, which hinders the precision of both. This degeneracy is most effectively addressed by assuming knowledge of one bias or targeting an optimal redshift range of $\displaystyle 1 \lt z \lt 2.5$. Our analysis opens new avenues for studying the distribution of BBHs and testing the nature of gravity through large-scale structure.

Zazzera, Stefano (ORCID:0000000158979221)↗

Chapter 4: Physically informed deep learning networks for simulating microstructure evolution of 3D polycrystals

As discussed in the previous chapter, high energy diffraction microscopy (HEDM) is used to study the micromechanical evolution of a material during in situ loading. HEDM experiments have been used to verify crystal plasticity (CP) simulations [119, 91, 90, 120], for experimental planning, material design, and to further analyze experimental results. However, Fast Fourier transform-based CP (CP-FFT) or finite element-based CP (CP-FE) methods are often too slow to be used in real-time during an experiment. CP-FFT is faster than CP-FE simulations due to the absence of meshing, but can still take hours to simulate the response of a single volume depending on the size and number of strain steps [127]. Reducing computation time would create a larger exploration space in planning and design, and enable faster analysis of experimental results and real-time feedback during an experiment. This research expands upon previous works to develop a workflow for predicting the full-field evolution of a 3D polycrystal. The workflow is simplified from previous works to predict only orientation and elastic strain tensors (from which stress tensors are calculated). The network is physically informed through loss functions and network architecture for a more robust model. The orientation predictions are informed about the cubic crystal symmetry of the material by incorporating disorientation and misorientation information into the network architecture and loss. The Von Mises stress is used to enforce the correct stress-strain trends in the strain tensor predictions. Additional total strain steps from the elastic and elastoplastic region are included to better capture the stress-strain evolution at smaller total strain steps. Material and hardening parameters are additional inputs into the networks to further inform the network and to study the network’s ability to predict different materials other than those used for training.

36 MATERIALS SCIENCE↗

A Parametric Battery Model for the Conceptual Design of Electric Aircraft

Electric aircraft conceptual designs usually have an assumed specific power and specific energy for the aircraft’s energy storage system that dictates the total capacity and the peak power available. The specific energy and power are inherently linked to the state-of-charge and discharge rate from which they were derived; therefore, they will not directly correspond to the diverse circumstances encountered in various aircraft missions and flight segments. These parameters turn the battery system into a black box, disregard potential electrical restrictions, and disallow the aircraft and battery to be optimized as a system. Peering into this box, this study highlights the importance of incorporating a parametric battery model into the conceptual design workflow by splitting high-level terms such as power into voltage and current and investigating their variability during the discharge process. Through the modeling of these more detailed parameters, this methodology shows the feasibility of using low states-of-charge for contingency operations, including the end of the reserve mission, expanding the amount of usable capacity for electric aircraft. Stark differences in aircraft capabilities can arise between varying fidelity battery models due to late-mission, high-power flight operations. This parametric battery model effectively captures these differences by evaluating the limitations that arise within the individual battery cells and the aircraft powertrain. This paper shows that the unusable charge of a battery is set by the balked landing power requirement and can realistically range from 5% to 44% based on assumptions. This sets the analog to unusable fuel capacity in aircraft with liquid fuel systems. Needing only aircraft- and mission-level inputs and only seconds of run time, this model is a prime fit for the fast, accurate exploration of the electric aircraft conceptual design space.

Battery↗

Fully Distributed Multi-Material Magnetic Sensing Structures for Multiparameter DAS Applications

This dissertation demonstrates the first of its kind distributed magnetic field sensor based on a fiber optic distributed acoustic sensing (DAS) scheme. Ferromagnetic nickel and Metglas® were dispersed internally within a fiber optic preform and then drawn on an in-house fiber optic draw tower to lengths in the kilometers. Due to the close proximity of the ferromagnetic metals and fiber optic core, the magnetostrictive strain response of the ferromagnetic materials when exposed to a magnetic field would perturbate within the fiber cladding and transfer that strain, internally, to the fiber optic core. Strain resulting from the magnetostrictive effect allows the DAS based sensor to accurately translate strain into readable magnetic field data. Due to the high sensitivity seen in this sensor design, multiparameter sources, acoustic and magnetic fields, were tested and validated and a three dimensional magnetic-field vector sensor was proposed. Numerical analysis of the novel sensor design was first implemented using COMSOL Multiphysics, where inputs such as magnetostrictive element shape, size, distance, and number were first investigated. Upon optimizing system constraints, the sensor design was further modified such that single mode operation was consistent across multiple fiber draws while retaining high strain transfer from the ferromagnetic elements to the fiber optic core. Ferromagnetic material selection was evaluated as a function of the saturation magnetostriction constants and a total of 4 modules were used to fully characterize the complex physics involved in this sensor design. All fabrication and testing were performed in-house using a full scale 3-story fiber draw tower and custom environmental testing stations to imitate naturally occurring events such as magnetic or acoustic point sources. A unique stacking method was used to embed ferromagnetic nickel and Metglas® into a fiber optic preform which when combined with a custom fiber draw process resulted in consistent multi-material fibers drawn to lengths of 1-km. In-house testing facilities included different types of electromagnetic generators, in addition to a soil test bed, and an outdoor test bed which allowed 100 meters of fiber to be tested simultaneously. All tested sensors demonstrated high strain transfer capabilities on the order of 0.01-10 μϵ depending on the materials used, ferromagnetic rod number, and core to metal spacing. Due to the sensitivity of the system the difference between AC and DC was distinct, and directional magnetostriction was studied. Transverse and longitudinal magnetic wave propagation was controlled through a solenoid and rectangular Helmholtz coil, both built in-house. A three-dimensional magnetic field vector sensor was proposed due to the success of the magnetic field sensor, and a design was proposed and initially tested to validate direction as a function of field strength and distance. To summarize, this dissertation explores the first fully distributed magnetic field sensor using DAS based techniques and one of the first multi-material fiber draw processes which can produce consistent single mode fiber up to 1-km. Due to extensive FEA modeling, multiple iterations of the magnetic sensor were fully characterized and an equation describing the relationship between sensor design and strain transfer has been created and validated experimentally. Multi-parameter tests including acoustic and magnetic fields were implemented and an algorithm was developed to separate the mixed signals. Finally, a test was performed to demonstrate the feasibility of sensing magnetic fields directionally. Cumulative results demonstrate a high-quality sensor alternative to current designs which may surpass other magnetic sensors due to innate multi-parameter capabilities, in addition to the inexpensive production cost and extremely long operating lengths.

02 PETROLEUM↗

Hijacking a rapid and scalable metagenomic method reveals subgenome dynamics and evolution in polyploid plants

Premise: The genomes of polyploid plants archive the evolutionary events leading to their present forms. However, plant polyploid genomes present numerous hurdles to the genome comparison algorithms for classification of polyploid types and exploring genome dynamics. Methods: Here, the problem of intra- and inter-genome comparison for examining polyploid genomes is reframed as a metagenomic problem, enabling the use of the rapid and scalable MinHashing approach. To determine how types of polyploidy are described by this metagenomic approach, plant genomes were examined from across the polyploid spectrum for both k-mer composition and frequency with a range of k-mer sizes. In this approach, no subgenome-specific k-mers are identified; rather, whole-chromosome k-mer subspaces were utilized. Results: Given chromosome-scale genome assemblies with sufficient subgenome-specific repetitive element content, literature-verified subgenomic and genomic evolutionary relationships were revealed, including distinguishing auto- from allopolyploidy and putative progenitor genome assignment. The sequences responsible were the rapidly evolving landscape of transposable elements. An investigation into the MinHashing parameters revealed that the downsampled k-mer space (genomic signatures) produced excellent approximations of sequence similarity. Furthermore, the clustering approach used for comparison of the genomic signatures is scrutinized to ensure applicability of the metagenomics-based method. Discussion: The easily implementable and highly computationally efficient MinHashing-based sequence comparison strategy enables comparative subgenomics and genomics for large and complex polyploid plant genomes. Such comparisons provide evidence for polyploidy-type subgenomic assignments. In cases where subgenome-specific repeat signal may not be adequate given a chromosomes' global k-mer profile, alternative methods that are more specific but more computationally complex outperform this approach.

59 BASIC BIOLOGICAL SCIENCES↗

Effect of the space weather conditions on the Earth magnetosphere soft X-ray emissivity

The aim of the study is to model and characterize the soft X-ray emissivity on the Earth magnetosphere for different space weather conditions (SWC), providing information to interpret the soft X-ray measurements of the Solar wind Magnetosphere Ionosphere Link Explorer space mission. The MHD code pluto in spherical coordinates is used to perform parametric studies with respect to the solar wind (SW) dynamic pressure (considering density and velocity effects independently) as well as the IMF intensity and orientation, predicting the soft X-ray emissivity for different SWC. The integrated soft X-ray emissivity inside the magnetosheath is calculated as a proxy of the soft X-ray emission dependencies with the SWC independently of the satellite orbit and camera line of sight. The analysis indicates fluctuations of the interplanetary magnetic field (IMF) orientation and magnitude may significantly affect the measured soft X-ray emission although changes in the SW dynamic pressure should be the main source of variability. The southward IMF orientation leads to the configuration with the largest soft X-ray emissivity and northward to the lowest. Strongly distorted magnetospheres explored in configurations showing SW and IMF parameters comparable to the impact of interplanetary coronal mass ejections may show a decrease of the soft X-ray emissivity as the IMF magnitude increases, explained by the strong magnetosphere compression and constriction of the magnetosheath region where the soft X-ray emissivity maximum is located. The simulations also indicate large excursions of the soft X-ray emissivity maximum inside the magnetosheath as the IMF magnitude and SW dynamic pressure fluctuate particularly for radial and ecliptic IMF orientations.

Earth↗