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At least 1,783 records · Page 99

A Radiation Chemistry Code Based on the Greens Functions of the Diffusion Equation

Ionizing radiation produces several radiolytic species such as.OH, e-aq, and H. when interacting with biological matter. Following their creation, radiolytic species diffuse and chemically react with biological molecules such as DNA. Despite years of research, many questions on the DNA damage by ionizing radiation remains, notably on the indirect effect, i.e. the damage resulting from the reactions of the radiolytic species with DNA. To simulate DNA damage by ionizing radiation, we are developing a step-by-step radiation chemistry code that is based on the Green's functions of the diffusion equation (GFDE), which is able to follow the trajectories of all particles and their reactions with time. In the recent years, simulations based on the GFDE have been used extensively in biochemistry, notably to simulate biochemical networks in time and space and are often used as the "gold standard" to validate diffusion-reaction theories. The exact GFDE for partially diffusion-controlled reactions is difficult to use because of its complex form. Therefore, the radial Green's function, which is much simpler, is often used. Hence, much effort has been devoted to the sampling of the radial Green's functions, for which we have developed a sampling algorithm This algorithm only yields the inter-particle distance vector length after a time step; the sampling of the deviation angle of the inter-particle vector is not taken into consideration. In this work, we show that the radial distribution is predicted by the exact radial Green's function. We also use a technique developed by Clifford et al. to generate the inter-particle vector deviation angles, knowing the inter-particle vector length before and after a time step. The results are compared with those predicted by the exact GFDE and by the analytical angular functions for free diffusion. This first step in the creation of the radiation chemistry code should help the understanding of the contribution of the indirect effect in the formation of DNA damage and double-strand breaks.

Plante, Ianik↗

Simulation Evaluations of an Autonomous Urban Air Mobility Network Management and Separation Service

This paper presents an initial implementation of an autonomous Urban Air Mobility network management and aircraft separation service for urban airspace that does 1) departure and arrival scheduling across the network, 2) continuous trajectory management to ensure safe separation between aircraft, and 3) seamless integration with traditional operations. The highly-autonomous AutoResolver algorithm developed for traditional aviation was extended to provide these capabilities. An evaluation of this initial implementation was conducted in fast-time simulations using a dense, two-hour traffic scenario with Urban Air Mobility aircraft flying between a network of 20 vertiports in the Dallas-Fort Worth metroplex. When the spatial separation was reduced from 0:3nmi to 0:1nmi, the total de- lay decreased by 7:3%; when the temporal separation was reduced from 60s to 45s, the total delay decreased by 28:4%. The total number of conflict resolutions decreased by 26% and 17%, respectively. Furthermore, when a scheduling horizon greater than the duration of UAM flights was used (50min), most conflicts were resolved pre-departure producing ground delay. By comparison, when a shorter scheduling horizon was used (8min), most conflicts were resolved post-departure generating airborne delay. For all scheduling and separation constraints tested, AutoResolver prevented loss of separation from occurring. Urban Air Mobility operations have the ability to revolutionize how people and goods are transported and this paper presents initial research focusing on the high levels of autonomy required for an airspace system capable of scaling to handle significantly higher densities of aircraft.

Bosson, Christabelle S.↗

Analytical investigations in aircraft and spacecraft trajectory optimization and optimal guidance

A collection of analytical studies is presented related to unconstrained and constrained aircraft (a/c) energy-state modeling and to spacecraft (s/c) motion under continuous thrust. With regard to a/c unconstrained energy-state modeling, the physical origin of the singular perturbation parameter that accounts for the observed 2-time-scale behavior of a/c during energy climbs is identified and explained. With regard to the constrained energy-state modeling, optimal control problems are studied involving active state-variable inequality constraints. Departing from the practical deficiencies of the control programs for such problems that result from the traditional formulations, a complete reformulation is proposed for these problems which, in contrast to the old formulation, will presumably lead to practically useful controllers that can track an inequality constraint boundary asymptotically, and even in the presence of 2-sided perturbations about it. Finally, with regard to s/c motion under continuous thrust, a thrust program is proposed for which the equations of 2-dimensional motion of a space vehicle in orbit, viewed as a point mass, afford an exact analytic solution. The thrust program arises under the assumption of tangential thrust from the costate system corresponding to minimum-fuel, power-limited, coplanar transfers between two arbitrary conics. The thrust program can be used not only with power-limited propulsion systems, but also with any propulsion system capable of generating continuous thrust of controllable magnitude, and, for propulsion types and classes of transfers for which it is sufficiently optimal the results of this report suggest a method of maneuvering during planetocentric or heliocentric orbital operations, requiring a minimum amount of computation; thus uniquely suitable for real-time feedback guidance implementations.

Markopoulos, Nikos↗

GRYPHON: Air launched space booster

The project chosen for the winter semester Aero 483 class was the design of a next generation Air Launched Space Booster. Based on Orbital Sciences Corporation's Pegasus concept, the goal of Aero 483 was to design a 500,000 pound air launched space booster capable of delivering 17,000 pounds of payload to Low Earth Orbit and 8,000 pounds of payload to Geosynchronous Earth Orbit. The resulting launch vehicle was named the Gryphon. The class of forty senior aerospace engineering students was broken down into eight interdependent groups. Each group was assigned a subsystem or responsibility which then became their field of specialization. Spacecraft Integration was responsible for ensuring compatibility between subsystems. This group kept up to date on subsystem redesigns and informed those parties affected by the changes, monitored the vehicle's overall weight and dimensions, and calculated the mass properties of the booster. This group also performed the cost/profitability analysis of the Gryphon and obtained cost data for competing launch systems. The Mission Analysis Group was assigned the task of determining proper orbits, calculating the vehicle's flight trajectory for those orbits, and determining the aerodynamic characteristics of the vehicle. The Propulsion Group chose the engines that were best suited to the mission. This group also set the staging configurations for those engines and designed the tanks and fuel feed system. The commercial satellite market, dimensions and weights of typical satellites, and method of deploying satellites was determined by the Payloads Group. In addition, Payloads identified possible resupply packages for Space Station Freedom and identified those packages that were compatible with the Gryphon. The guidance, navigation, and control subsystems were designed by the Mission Control Group. This group identified required tracking hardware, communications hardware telemetry systems, and ground sites for the location of the Gryphon's mission control center. The Structures group was responsible for ensuring the structural integrity of the vehicle. Their designs included the payload shroud, payload support structure, exterior hull and engine support struts. The Gryphon's power requirements were determined by the Power/Thermal/Attitude Control Group. This group then selected suitable batteries and other components to meet these requirements. The group also designed heat shielding and cooling systems to ensure subsystem performance. In addition to these responsibilities this group designed the attitude control methods and RCS components for the vehicle. The Aircraft Integration Group was responsible for all aspects of the booster aircraft connection. This included the design of the connection structure and the drop mechanism. This group also designed the vehicle assembly facility and identified possible ground bases for the plane.

Source record↗

Stability-Constrained Learning for Frequency Regulation in Power Grids With Variable Inertia

The increasing penetration of converter-based renewable generation has resulted in faster frequency dynamics, and low and variable inertia. As a result, there is a need for frequency control methods that are able to stabilize a disturbance in the power system at timescales comparable to the fast converter dynamics. This paper proposes a combined linear and neural network controller for inverter-based primary frequency control that is stable at time-varying levels of inertia. We model the time-variance in inertia via a switched affine hybrid system model. We derive stability certificates for the proposed controller via a quadratic candidate Lyapunov function. We test the proposed control on a 12-bus 3-area test network, and compare its performance with a base case linear controller, optimized linear controller, and finite-horizon Linear Quadratic Regulator (LQR). Our proposed controller achieves faster mean settling time and over 50% reduction in average control cost across 100 inertia scenarios compared to the optimized linear controller. Unlike LQR which requires complete knowledge of the inertia trajectories and system dynamics over the entire control time horizon, our proposed controller is real-time tractable, and achieves comparable performance to LQR.

data-driven control↗

SA13B-1900 Auroral Charging of the International Space Station

Electrostatic potential variations of the International Space Station (ISS) relative to the space plasma environment are dominated by interaction of the negatively grounded 160 volt US photovoltaic power system with the plasma environment in sunlight and inductive potential variations across the ISS structure generated by motion of the vehicle across the Earth's magnetic field. Auroral charging is also a source of potential variations because the 51.6? orbital inclination of ISS takes the vehicle to sufficiently high magnetic latitudes to encounter precipitating electrons during geomagnetic storms. Analysis of auroral charging for small spacecraft or isolated insulating regions on ISS predict rapid charging to high potentials of hundreds of volts but it has been thought that the large capacitance of the entire ISS structure on the order of 0.01 F will limit frame potentials to less than a volt when exposed to auroral conditions. We present three candidate auroral charging events characterized by transient ISS structure potentials varying from approximately 2 to 17 volts. The events occur primarily at night when the solar arrays are unbiased and cannot therefore be due to solar array current collection. ISS potential decreases to more negative values during the events indicating electron current collection and the events are always observed at the highest latitudes along the ISS trajectory. Comparison of the events with integral >30 keV electron flux measurements from NOAA TIROS spacecraft demonstrate they occur within regions of precipitating electron flux at levels consistent with the energetic electron thresholds reported for onset of auroral charging of the DMSP and Freja satellites. In contrast to the DMSP and Freja events, one of the ISS charging events occur in sunlight.

Minow, Joseph I.↗

Climate change penalty and benefit on surface ozone: a global perspective based on CMIP6 earth system models

Abstract This work presents an analysis of the effect of climate change on surface ozone discussing the related penalties and benefits around the globe from the global modelling perspective based on simulations with five CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System Models. As part of AerChemMIP (Aerosol Chemistry Model Intercomparison Project) all models conducted simulation experiments considering future climate (ssp370SST) and present-day climate (ssp370pdSST) under the same future emissions trajectory (SSP3-7.0). A multi-model global average climate change benefit on surface ozone of −0.96 ± 0.07 ppbv °C −1 is calculated which is mainly linked to the dominating role of enhanced ozone destruction with higher water vapour abundances under a warmer climate. Over regions remote from pollution sources, there is a robust decline in mean surface ozone concentration on an annual basis as well as for boreal winter and summer varying spatially from −0.2 to −2 ppbv °C −1 , with strongest decline over tropical oceanic regions. The implication is that over regions remote from pollution sources (except over the Arctic) there is a consistent climate change benefit for baseline ozone due to global warming. However, ozone increases over regions close to anthropogenic pollution sources or close to enhanced natural biogenic volatile organic compounds emission sources with a rate ranging regionally from 0.2 to 2 ppbv C −1 , implying a regional surface ozone penalty due to global warming. Overall, the future climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions and thus the magnitude of this effect depends on the regional emission changes considered in this study within the SSP3_7.0 scenario. The comparison of the climate change impact effect on surface ozone versus the combined effect of climate and emission changes indicates the dominant role of precursor emission changes in projecting surface ozone concentrations under future climate change scenarios.

Zanis, Prodromos↗

Coal-dependent Communities in Transition: Identifying Best Practices to Ensure Equitable Outcomes

The U.S. coal industry is experiencing a sharp increase in the numbers of retired and/or decommissioned coal-fired power plants across the U.S. In the years between 2010-2019, around 102 gigawatts (GW) of coal-fired generating capacity has been announced to be decommissioned, representing more than 546 coal-fired power plant units, and an additional 17 GW is planned to be decommissioned by 2025. This change in the energy production landscape presents an impact on the social, environmental, and economic prospects of coal-dependent communities. This report examined the role of communities in the coal power plant decommissioning process and provided community-identified best practices to ensure an equitable process. The experiences of four coal-dependent communities—Wise County, VA, Muskegon, MI, Anderson County, TN, and Becker, MN—are presented as case studies to understand the impacts of the decommissioning process, and associated best practices, from the communities’ perspective. The report results highlight the need to recognize that the decommissioning decision-making process must be community-based to be equitable. Each community’s input is key to the transition away from coal power because there is no one-size-fits-all development plan. In other words, each community’s trajectory through the decommissioning process—from the retirement decision-making stage to the final site redevelopment phase—is unique because each community has distinct needs and wants from the energy transition. What is best for one community may not be suited for another. Ultimately, the framework for site development and community revitalization post-decommissioning cannot be universal because each community’s profile—from a social, cultural, and economic perspective—is different. Community impacts of power plant decommissioning are not limited to job and revenue losses. Communities are likely to be impacted culturally, socially, environmentally, and have long-term health-based impacts that should be acknowledged and addressed in post-retirement plans. Commonly identified decommissioning best practices include: Early and continued engagement throughout, with a number of mediums for communication and feedback (e.g., in-person sessions, virtual meetings, written comment opportunities); Early planning of post-decommissioning projects to replace lost jobs, revenue, and economic activity; Recognition (and mitigation, if possible) of social impacts on the community due to plant closure; Transparency throughout the process, with trusted information being provided about the decommissioning process and timeline; potential impacts on the workforce, economy, and environment; and the feasibility of alternative site uses; Identification of funding sources, technical experts, and/or strategic partnerships to support decommissioning and the affected communities upfront; and, Acknowledgment of communities as stakeholders who have a role in the conversation and right to determine their futures. Three key areas for assisting coal-dependent communities affected by the energy transition: Technical assistance: assessment of site feasibility for alternative uses or to repower with new technologies; Cross-partnership engagement and collaboration: facilitate knowledge-sharing of “lessons learned” about the decommissioning process between communities and provide guidance for decision-making processes; and, Financial assistance: access to grant and/or loan programs to assist with redevelopment survey, bolster community economic security through job creation, and cover environmental clean-up costs. Technical assistance, cross-partnership engagement, and financial aid can be mobilized to help communities throughout various stages of the decommissioning process, including the retirement decision, the site reclamation phase, and eventual revitalization of the site and surrounding community.

01 COAL, LIGNITE, AND PEAT↗

Fusion-Enabled Pluto Orbiter and Lander

Direct Fusion Drive (DFD) is a unique fusion engine concept based on the Princeton Field-Reversed Configuration (PFRC) fusion reactor conceived by Dr. Sam Cohen of the Princeton Plasma Physics Laboratory. DFD would enable the Pluto orbiter and lander context mission and more broadly enable true "rapid transit" to outer-planet and near interstellar space. The truly game-changing levels of thrust and power in a modestly sized package could integrate with our current launch infrastructure while radically expanding the science capability of these missions. Our Phase I was our first funded work on the DFD, with previous work at PSS occurring only under internal R&D. We established the feasibility of our Pluto mission trajectories using straight-line and planar models, including a departure spiral from Earth and insertion at Pluto. We developed our first thrust and specific impulse model using the results of the UEDGE multi-fluid code. Our specific power model was improved. During this Phase II effort, we continued our efforts to increase the fidelity of the designs for the RF, magnet, and shielding subsystems. Dedicated thrust augmentation experiments were run on the PFRC experiment, using a supersonic gas puffing valve. For the first time, we analyzed the design of a closed-loop operation mode and estimated the hardware that would be required for a dual-mode engine. In an exciting new development, we have invented a new thermophotovoltaic thermal conversion method that has the potential to have efficiencies of a Brayton or Stirling system. Our report presents details of these analyses. Our roadmap to bringing DFD to flight predicts that with sufficient support, a first flight unit could be built by 2040. We anticipate that three machine generations are required before this point: a ~1 T PFRC-3 machine hitting new plasma temperature and density levels, a ~5 T PFRC-4 machine with first demonstration of D-3He fusion, and a flight. (The current experiment, PFRC-2, is limited to about 0.1 T). In order to achieve a flight in 2035-2040, the TRL of the supporting systems must be increased in parallel, including low mass radiators, cryogenic propellant storage, and large (>100 kW) thermal conversion systems. Fortunately, many of these systems are dual-use and are required for other technologies including fission systems, so DFD would contribute to and benefit from those programs. This NIAC support and the results of our work have led to multiple follow-on contracts. We won two NASA STTRs focused on DFD subsystems, one on the RF system and one on the superconducting magnets, and our magnet STTR is now midway through a Phase II. We will be receiving a superconducting test magnet for experiments at PPPL this summer. In addition, we won an ARPA-E OPEN grant; this is the first time that OPEN has included fusion technologies, and we are part of a cohort of three alternative fusion companies now supported directly by DOE. We are very optimistic that if we are able to meet our experimental milestones in the next 12-18 months, we will be competitive for additional DOE grants to build PFRC-3.

Propulsion↗

Climate Change Penalty and Benefit on Surface Ozone: A Global Perspective Based on CMIP6 Earth System Models

This work presents an analysis of the effect of climate change on surface ozone discussing the related penalties and benefits around the globe from the global modelling perspective based on simulations with five CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System Models. As part of AerChemMIP (Aerosol Chemistry Model Intercomparison Project) all models conducted simulation experiments considering future climate (ssp370SST) and present-day climate (ssp370pdSST) under the same future emissions trajectory (SSP3-7.0). A multi-model global average climate change benefit on surface ozone of −0.96 ± 0.07 ppbv °C−1 is calculated which is mainly linked to the dominating role of enhanced ozone destruction with higher water vapour abundances under a warmer climate. Over regions remote from pollution sources, there is a robust decline in mean surface ozone concentration on an annual basis as well as for boreal winter and summer varying spatially from −0.2 to −2 ppbv °C−1, with strongest decline over tropical oceanic regions. The implication is that over regions remote from pollution sources (except over the Arctic) there is a consistent climate change benefit for baseline ozone due to global warming. However, ozone increases over regions close to anthropogenic pollution sources or close to enhanced natural biogenic volatile organic compounds emission sources with a rate ranging regionally from 0.2 to 2 ppbv C−1, implying a regional surface ozone penalty due to global warming. Overall, the future climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions and thus the magnitude of this effect depends on the regional emission changes considered in this study within the SSP3_7.0 scenario. The comparison of the climate change impact effect on surface ozone versus the combined effect of climate and emission changes indicates the dominant role of precursor emission changes in projecting surface ozone concentrations under future climate change scenarios.

surface ozone↗

Crystal Ball: A Naturalist Perspective of Microbiology: Examples from Methanogenic Archaea

Storytelling has been the primary means of knowledge transfer over human history. The effectiveness and reach of stories are improved when the message is appropriate for the target audience. Oftentimes, the stories that are most well received and recounted are those that have a clear purpose and that are told from a variety of perspectives that touch on the varied interests of the target audience. Whether scientists realize or not, they are accustomed to telling stories of their own scientific discoveries through the preparation of manuscripts, presentations, and lectures. Perhaps less frequently, scientists prepare review articles or book chapters that summarize a body of knowledge on a given subject matter, meant to be more holistic recounts of a body of literature. Yet, by necessity, such summaries are often still narrow in their scope and are told from the perspective of a particular discipline. In other words, interdisciplinary reviews or book chapters tend to be the rarity rather than the norm. Naturalists are scientists that tell stories of organisms and their natural environment within a historical context and from an interdisciplinary perspective. Such stories interweave observations of biological subjects from disparate disciplines into a cohesive story. To this end, the success of naturalists in recounting compelling natural history stories is enhanced when they allow themselves to become vulnerable by knowingly entering a literature base full of unfamiliar ways of observing and describing such subjects. When successful, this approach can broaden the scope of the story, making it of interest to a larger audience and attracting further recounting of that story (e.g., citations). To this end, when we look into our crystal ball, we see a need to tell more holistic stories of microorganisms and their functions from an interdisciplinary, naturalist perspective that combines what is known of their contemporary ecology, physiology, and biochemistry with their evolutionary history thereby placing them within a historical Earth context. With this conviction in mind, we take the opportunity to look back on the natural history of methanogens to identify some of their most profound biochemical innovations and their impact on the trajectory of life and the planet. Our approach was to integrate knowledge from the fields of biochemistry, physiology, ecology, evolution, geochemistry, and atmospheric sciences. We start with the origin of the first autotrophic cells and how this set Earth on a path towards biomass expansion and functional diversification. Next, we discuss the importance of iron and sulfur in methanogen metabolism, and how their innovative ways of accessing these elements allowed for expanded use of iron-sulfur clusters ([Fe-S]) as nanoscale catalysts that power(ed) Earth’s biochemical cycles. We next discuss the origin and evolution of [NiFe]-hydrogenase and how this versatile enzyme chassis was co-opted by a variety of anaerobes and aerobes as the foundation for respiratory complexes capable of sustaining higher forms of life, including humans. Lastly, we discuss the evolution of the enzyme molybdenum nitrogenase, and how this allowed the biosphere to overcome fixed nitrogen limitation by tapping the seemingly endless reserve of atmospheric dinitrogen (N 2 ). In telling these stories, we aimed to generate template(s) to motivate future interdisciplinary natural history studies focused on other organisms and processes. Further, we hope to stimulate scientific discourse and provide impetus to become vulnerable and peruse literature of relevance to understanding the causes and consequences of the evolution of your favorite microorganism or biochemical process.

59 BASIC BIOLOGICAL SCIENCES↗

Fermi-type particle acceleration from magnetic reconnection at the termination shock of a relativistic striped wind

An oblique-rotating pulsar generates a relativistic striped wind in a pulsar wind nebula (PWN). The termination shock of the PWN compresses the Poynting-flux-dominated flow and drives magnetic reconnection. By carrying out particle-in-cell simulations of the termination shock of the PWN, we study the shock structure as well as the energy conversion processes and particle acceleration mechanisms. With the recent advances in the numerical methods, we extend the simulations to the ultrarelativistic regime with a bulk Lorentz factor of up to γ 0 = 10 6 . Magnetic reconnection at the termination shock is highly efficient at converting magnetic energy to particle kinetic energy and accelerating particles to high energies. Similar to earlier studies, we find that the resulting energy spectra crucially depend on λ/d e (λ is the wavelength of the striped wind and de is the relativistic plasma skin depth). When λ/d e is large (λ ≳ 40d e ), the downstream particle spectra form a power-law distribution in the magnetically dominated relativistic wind regime. By analyzing particle trajectories and statistical quantities relevant to particle energization, we find that Fermi-type mechanism dominates the particle acceleration and power-law formation. We find that the results for particle acceleration are scalable as γ 0 and σ 0 increase to large values. The maximum energy for electrons and positrons can reach hundreds of TeV if the wind has a bulk Lorentz factor of γ0 ≈ 106 and a magnetization parameter of σ 0 = 10, which can explain the recent observations of high-energy gamma rays from PWNe

79 ASTRONOMY AND ASTROPHYSICS↗

Scenario Complexity for Unmanned Aircraft System Traffic

This work introduces an approach to estimate the complexity of a low-altitude air traffic scenario involving multiple UASs using mathematical programming. Given a set of multi-point UAS flight trajectories, vehicle dynamics, and a conflict resolution algorithm, an abstract model is developed such that it can be solved quickly using a mathematical programming optimization software without running high-fidelity simulations that can be computationally expensive and may not suit real-time apA quick and accurate assessment of complexity for a given traffic scenario can help plan and schedule flights to alleviate traffic bottleneck and mitigate operation risks, especially for unmanned aerial system traffic management where high traffic density or complexity is expected. This work introduces a traffic scenario complexity metric that was constructed based on the number of potential conflicts weighted by the conflict resolution cost associated. The cost associated with a conflict is calculated based on the corresponding conflict resolution maneuvers. To obtain the conflict resolution maneuvers, a MILP-based optimization was formulated with the vehicle model and conflict management parameters incorporated. To evaluate the complexity metrics, an approach of using measurements from high-fidelity simulations was proposed. The scenario complexity measurements for 920 random-generated scenarios were obtained through high-fidelity simulations and treated as the ground truth. Two statistics methods: Pearson and Alternative Conditional Expectations were applied for analysis. The results showed that the number of flights has low correlation with the scenario complexity according to the correlation coefficients calculated by both methods. The Alternative Conditional Expectations method shows that the proposed scenario complexity metric has better correlation with the ground truth than the number of potential conflicts.plications. In the abstract model, each vehicle is represented by a time-varied vector associated with position, speed, and heading information. The total extra distance that aircraft need to divert from their original routes to avoid collisions is computed and used to setup a quadratic programming formula. The metrics including the number of conflicts and extra distances travelled by all vehicles are then utilized to estimate the complexity of a given UAS flight scenario. Results and verification against high-fidelity simulations will be provided in the final draft.

traffic complexity↗

A Novel Bone Marrow Single Cell Atlas of Mechanotransduction in Microgravity, Normal Gravity, Exercise, and Hindlimb Unloading for WT and CDKN1A-Null Regenerative Mice

Mechanical loading of adult stem cell progenitors is a key factor in modulating their proliferation, differentiation, and tissue regenerative potential, with loading generally promoting tissue formation and unloading mediating tissue loss. To address the role of mechanotransduction in maintaining stem cell-based tissue regenerative health, we generated a single cell transcriptomic atlas mapping responses of femur bone marrow mesenchymal and hematopoietic lineages to a range of altered mechanical loading conditions, both in WT B1629SF2/J mice as well as the p21/CDKN1A-null regenerative mice. We selected the femur marrow compartment as a model because of the diversity and high numbers of stem cell progenitor stages present, and because it undergoes static and cyclic hydrostatic pressure loading associated with weight-bearing and ambulation. Our study included normally loaded mice at 1g, unloading in microgravity during spaceflight as well as tail suspension hindlimb unloading, and voluntary running wheel exercise. Basal, one-year natural aging, and habitat controls were also conducted. Overall, the atlas encompasses 18 different experimental conditions with N=3 mice per condition and includes more than 500,000 single cell expressomes. Key specific findings include: increased mature reticulocyte populations in aging and unloading mice compared to active mice; greater hematopoietic and mesenchymal differentiating progenitors cluster identification in CDKN1A-null samples, especially the exercise model; distinct pseudotime cell trajectory shifts in the hematopoietic lineage for spaceflight and unloaded mice; and shifts in monocytic cell populations toward osteoclastic bone degenerative lineages in unloading and spaceflight samples. Overall mechanical loading shows increased marrow progenitor population differentiation while unloading is associated with increased CDKN1A expression and maintenance of marrow population stemness. Deletion of CDKN1A appears to remove a negative check on progenitor lineages commitment to differentiation. Finally, the Bone Marrow Mechanotransduction Single Cell Atlas will serve as a reference tool for studying marrow regenerative responses across a range of mechanical environments as they relate to CDKN1A status.

single-cell↗

Creation of a Rapid High-Fidelity Aerodynamics Module for a Multidisciplinary Design Environment

In the traditional aerospace vehicle design process, each successive design phase is accompanied by an increment in the modeling fidelity of the disciplinary analyses being performed. This trend follows a corresponding shrinking of the design space as more and more design decisions are locked in. The correlated increase in knowledge about the design and decrease in design freedom occurs partly because increases in modeling fidelity are usually accompanied by significant increases in the computational expense of performing the analyses. When running high fidelity analyses, it is not usually feasible to explore a large number of variations, and so design space exploration is reserved for conceptual design, and higher fidelity analyses are run only once a specific point design has been selected to carry forward. The designs produced by this traditional process have been recognized as being limited by the uncertainty that is present early on due to the use of lower fidelity analyses. For example, uncertainty in aerodynamics predictions produces uncertainty in trajectory optimization, which can impact overall vehicle sizing. This effect can become more significant when trajectories are being shaped by active constraints. For example, if an optimal trajectory is running up against a normal load factor constraint, inaccuracies in the aerodynamic coefficient predictions can cause a feasible trajectory to be considered infeasible, or vice versa. For this reason, a trade must always be performed between the desired fidelity and the resources available. Apart from this trade between fidelity and computational expense, it is very desirable to use higher fidelity analyses earlier in the design process. A large body of work has been performed to this end, led by efforts in the area of surrogate modeling. In surrogate modeling, an up-front investment is made by running a high fidelity code over a Design of Experiments (DOE); once completed, the DOE data is used to create a surrogate model, which captures the relationships between input variables and responses into regression equations. Depending on the dimensionality of the problem and the fidelity of the code for which a surrogate model is being created, the initial DOE can itself be computationally prohibitive to run. Cokriging, a modeling approach from the field of geostatistics, provides a desirable compromise between computational expense and fidelity. To do this, cokriging leverages a large body of data generated by a low fidelity analysis, combines it with a smaller set of data from a higher fidelity analysis, and creates a kriging surrogate model with prediction fidelity approaching that of the higher fidelity analysis. When integrated into a multidisciplinary environment, a disciplinary analysis module employing cokriging can raise the analysis fidelity without drastically impacting the expense of design iterations. This is demonstrated through the creation of an aerodynamics analysis module in NASA’s OpenMDAO framework. Aerodynamic analyses including Missile DATCOM, APAS, and USM3D are leveraged to create high fidelity aerodynamics decks for parametric vehicle geometries, which are created in NASA’s Vehicle Sketch Pad (VSP). Several trade studies are performed to examine the achieved level of model fidelity, and the overall impact to vehicle design is quantified.

Aerodynamic Properties↗

Phoenix - the First Mars Scout Mission

As the first of the new Mars Scouts missions, the Phoenix project was selected by NASA in August of 2003. Four years later, almost to the day, Phoenix was launched from Cape Canaveral Air Station and successfully injected into an interplanetary trajectory on its way to Mars. This paper will highlight some of the key changes since the 2006 IEEE paper of the same name, as well as activities, challenges and problems encountered on the way to the launch pad. Phoenix Follows the water responding directly to the recently published data from Dr. William Boynton, PI (and Phoenix co-I) of the Mars Odyssey Gamma Ray Spectrometer (GRS). GRS data indicate extremely large quantities of water ice (up to 50% by mass) within the upper 50 cm of the northern polar regolith. Phoenix will land within the north polar region at 68.2 N, 233.4 W identified by GRS to harbor near surface water ice and provide in-situ confirmation of this extraordinary find. Our mission will investigate water in all its phases, and will investigate the history of water as evidenced in the soil characteristics that will be carefully examined by the powerful suite of onboard instrumentation. Access to the critical subsurface region expected to contain this information is made possible by a third generation robotic arm capable of excavating the expected Martian regolith to a depth of 1m. Phoenix has four primary science objectives: 1) Determine the polar climate and weather, interaction with the surface, and composition of the lower atmosphere around 70 N for at least 90 sols focusing on water, ice, dust, noble gases, and CO2. Determine the atmospheric characteristics during descent through the atmosphere. 2) Characterize the geomorphology and active processes shaping the northern plains and the physical properties of the near surface regolith focusing on the role of water. 3) Determine the aqueous mineralogy and chemistry as well as the adsorbed gases and organic content of the regolith. Verify the Odyssey discovery of near-surface ice. 4) Characterize the history of water, ice, and the polar 1 1-4244-1488-1/08/$25.00 2008 IEEE 2 IEEEAC paper#1579, Version 1, Updated 2008:01:09 climate. Determine the past and present biological potential of the surface and subsurface environments.

Mars exploration↗

Dynamic motion trajectory control with nanoradian accuracy for multi-element X-ray optical systems via laser interferometry

The past decades have witnessed the development of new X-ray beam sources with brightness growing at a rate surpassing Moore’s law. Current and upcoming diffraction limited and fully coherent X-ray beam sources, including multi-bend achromat based synchrotron sources and high repetition rate X-ray free electron lasers, puts increasingly stringent requirements on stability and accuracy of X-ray optics systems. Parasitic motion errors at sub-micro radian scale in beam transport and beam conditioning optics can lead to significant loss of coherence and brightness delivered from source to experiment. To address this challenge, we incorporated optical metrology based on interferometric length and angle sensing and real-time correction as part of the X-ray optics motion control system. A prototype X-ray optics system was constructed following the optical layout of a tunable X-ray cavity. On-line interferometric metrology enabled dynamical feedback to a motion control system to track and compensate for motion errors. The system achieved sub-microradian scale performance, as multiple optical elements are synchronously and continuously adjusted. This first proof of principle measurement demonstrated both the potential and necessity of incorporating optical metrology as part of the motion control architecture for large scale X-ray optical systems such as monochromators, delay lines, and in particular, X-ray cavity systems to enable the next generation cavity-based X-ray free electron lasers.

47 OTHER INSTRUMENTATION↗

Particle Swarm Optimization Toolbox

The Particle Swarm Optimization Toolbox is a library of evolutionary optimization tools developed in the MATLAB environment. The algorithms contained in the library include a genetic algorithm (GA), a single-objective particle swarm optimizer (SOPSO), and a multi-objective particle swarm optimizer (MOPSO). Development focused on both the SOPSO and MOPSO. A GA was included mainly for comparison purposes, and the particle swarm optimizers appeared to perform better for a wide variety of optimization problems. All algorithms are capable of performing unconstrained and constrained optimization. The particle swarm optimizers are capable of performing single and multi-objective optimization. The SOPSO and MOPSO algorithms are based on swarming theory and bird-flocking patterns to search the trade space for the optimal solution or optimal trade in competing objectives. The MOPSO generates Pareto fronts for objectives that are in competition. A GA, based on Darwin evolutionary theory, is also included in the library. The GA consists of individuals that form a population in the design space. The population mates to form offspring at new locations in the design space. These offspring contain traits from both of the parents. The algorithm is based on this combination of traits from parents to hopefully provide an improved solution than either of the original parents. As the algorithm progresses, individuals that hold these optimal traits will emerge as the optimal solutions. Due to the generic design of all optimization algorithms, each algorithm interfaces with a user-supplied objective function. This function serves as a "black-box" to the optimizers in which the only purpose of this function is to evaluate solutions provided by the optimizers. Hence, the user-supplied function can be numerical simulations, analytical functions, etc., since the specific detail of this function is of no concern to the optimizer. These algorithms were originally developed to support entry trajectory and guidance design for the Mars Science Laboratory mission but may be applied to any optimization problem.

Grant, Michael J.↗