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At least 73 records · Page 4

Radiation and Nuclear Technology in Planetary Cave Environments

Many technological and environmental challenges must be resolved to enable successful lunar habitation and exploration, and to maximize scientific return. This presentation is intended as a preliminary discussion on three such areas of interest with the intent to identify likely areas of mutual benefit for collaboration and data sharing between the space nuclear and radiological disciplines with the planetary cave community. First is the previously identified and studied possible application of lunar lava tubes or pits to reduce the solar and cosmic radiation environment burden on crew health and hardware reliability. This is an area of continued interest, and should be kept in the forefront of discussion during the selection of sites for potential exploration or long-term habitation. In theory, the prospect of using existing morphology presents an enticing opportunity to reduce the requirements on landed mass or construction while also reducing dose or fluence of harmful natural radiation. However, such discussions should also include the practical implications of relocating habitation hardware and personnel from a landing site to a subsurface location. Inherent risks associated with landing in proximity to the relevant terrain must also be considered and weighed against those imposed by the natural radiation environment. Second is a discussion on the means by which a long-term habitation module or base of operations may be powered throughout the lunar day-night cycle. Fission surface power presents an opportunity to establish round-the-clock power in any lunar surface environment, including permanently shadowed regions where solar panels cannot operate, or in any other non-polar region where solar radiation is available for no more than two weeks per four-week cycle. Among the drawbacks of fission surface power is the need to either land and co-locate a heavy shield to minimize radiological consequences to personnel or equipment, land and operate construction equipment capable of restructuring the in-situ regolith to provide appropriate shielding, or to make use of existing topology features (e.g. craters or pits) to serve as pre-formed radiation barriers. A realistic assessment of the practicality of this third option should involve the selection of candidate features from existing surveys, and assess the effectiveness of the approach using modern radiation transport methodologies. Consideration must be made for the needs to reject waste heat in the thermal power conversion process, which typically requires the use of large area radiators. Energy must be exchanged from the reactor and power conversion system to such radiators, and the impacts on thermal efficiency and secondary scatter of nuclear radiation must be considered. Further consideration should be made for the implications of placement of a power source such that it does not sacrifice valuable scientific opportunity. Placement of a reactor is likely to thereafter prevent personnel access within that feature. Third is a discussion on the use of portable radioisotope power systems (RPS) within confined spaces, both with respect to the dose effects of emitted nuclear radiation and also performance associated with emitted thermal radiation. Radioisotope power systems provide a unique capability to power objects with no reliance upon solar radiance. However, their useable power production relies upon the flow of heat from ‘hot side’ (decaying radioisotope) to ‘cold side’ (radiators emitting heat to space). In the case of a confined volume in vacuum such as a lunar lava tube, that radiated energy will absorb into the wall, which is already above the ‘cold background’ temperature of dark space, and then gradually rises in temperature. That temperature rise, and its implications on availability of useable electrical power, will depend upon factors such as enclosure volume, thermal emissivity/absorptivity, and thermal conductivity through the depth of absorbing media. The advantages of nuclear technology may prove to enable unique scientific exploration opportunities, both above the lunar surface and below. In turn, the unique advantages of lunar lava tubes or pits may present unique opportunities to enhance the application of these technologies and to mitigate the effects of radiation from both natural and technological sources. A discussion on these pairings may prove to be valuable to all, in our endeavor to explore our neighboring worlds.

Radiation↗

Surface Qualification Toolpath Optimization for Hybrid Manufacturing

Hybrid manufacturing machine tools have great potential to revolutionize manufacturing by combining both additive manufacturing (AM) and subtractive manufacturing (SM) processes on the same machine tool. A prominent issue that can occur when going from AM to SM is that the SM process toolpath does not account for geometric discrepancies caused by the previous AM step, which leads to increased production times and tool wear, particularly when wire-based directed energy deposition (DED) is used as the AM process. This work discusses a methodology for approximating a part’s surface topology using on-machine contact probing and formulating an optimized SM toolpath using the surface topology approximation. Three different geometric surface approximations were used: triangular, trapezoidal, and a hybrid of both. SM toolpaths were created using each geometric approximation and assessed according to three objectives: reducing total machining time, reducing surface roughness, and reducing cutting force. Different prioritization scenarios of the optimization goals were also investigated. The optimal surface approximation that yielded the most improvement in the optimization was determined to be the hybrid surface topology approximation. Furthermore, it was shown that when the machining time or cutting force optimization goals were prioritized, there was little improvement in the other optimization goals.

36 MATERIALS SCIENCE↗

A novel design optimization framework to sustain remanufacturability

The ever-increasing global carbon emissions have urged the need for environmentally conscious/sustainable product design, for which the design for remanufacturing (DfRem) is one potential approach. DfRem targets at designing products that have multiple life cycles, thus significantly reducing raw material usage, energy consumption, and carbon emissions. In this paper, we develop a three-stage framework that consists of (1) systematic design space exploration and a multi-objective optimization formulation to minimize the likelihood of failure causes (such as fatigue and wear) and environmental footprint, (2) topology optimization to further reduce material usage without significantly affecting the load-carrying capability of the product, and (3) post-topology optimization design verification to ensure the proposed design satisfies all design constraints. The environmental impact can be assessed at varying comprehensiveness levels (e.g., design and manufacturing phase, use phase) and in terms of carbon or GHG emission, energy use, and waste generation. Because the novel design framework predominantly adjusted the geometry, we focused on mass-based change and energy savings due to sustained remanufacturability. The multi-objective optimization formulation in the first step results in a Pareto optimal set of possible design solutions that the designer can use for the second step. Finally, we demonstrate the utility of this framework through a case study of an engine cylinder head subjected to thermo-mechanical loads, where we find that about 5% of the product mass can be conserved with only about a 3% increase in surface area that has a fatigue life less than 10,000 cycles.

42 ENGINEERING↗

Characterization of micro-sandwich structures via direct ink writing epoxy based cores

Sandwich structured (SS) composites demonstrate considerable flexural stiffness and high strength-to-weight ratios and can be tailored as functional materials. Historically they have been constrained to specific material types and geometry due to limitations in manufacturing methods. However, employing additive manufacturing (AM), specifically direct ink writing (DIW), can provide an alternative method for making SS composites with complex and controllable micro and mesostructures with multifunctionality targeted at desired mechanical, thermal, and electrical properties. DIW, an extrusion-based AM technique, uses a viscous and thixotropic ink with desired components that, once printed, is cured to obtain the final complex net shape parts. In this paper, a novel hybrid AM technique is employed to manufacture SS composite materials containing bisphenol A-based epoxy core and carbon fiber reinforced polymer (CFRP) face sheets that are fabricated via DIW and vacuum infusion process (VIP), respectfully. We demonstrate that the fabrication of these SS composites can be tailored from a thermosetting material, from which additives and/or various lattice structures can be manufactured to achieve enhanced and desirable mechanical integrity with functional properties. Surface topology and mechanical testing techniques are used to characterize the fabricated hybrid SS composites to study and assess mechanical stability. A rheo-kinetic cure model was developed for the core material to allow for additive manufacturing process requirements while ensuring complete cross-linking for the thermoset-based core material. Because of the ability to obtain relatively small core-thickness and controlled architecture, this method now allows for fabricating layered micro-sandwich structures for realizing further light-weighting in relevant applications.

36 MATERIALS SCIENCE↗

Crosslink V.0.11.x User Manual

CrossLink is a novel two-dimensional and three-dimensional geometry and mesh generation software package developed by the Simulation Tools team at Los Alamos National Laboratory. This software represents the third generation of topology-based mesh generation technology developed by the Department of Defense and the Department of Energy with a special focus on complex multi-material hydrodynamic applications, mesh scalability, and high-order element mesh generation. The topology-based meshing approach offered by CrossLink enables users to quickly and easily mesh complex geometries in a repeatable and robust manner. CrossLink’s topology-based meshing approach is well-suited for parametric design studies, parametric design optimization, damage scenario assessment, and iterative design modification (i.e. feature addition and/or removal). CrossLink’s python API allows workflow scripting of the geometry creation and mesh generation process for traceability, repeatability, data provenance, and version control. CrossLink consists of three main components: a graphical user interface (GUI), a geometry creation and mesh generation engine, and a python API that provides a workflow scripting interface to the geometry and meshing functions.

97 MATHEMATICS AND COMPUTING↗

Transportation Network Topologies

A discomforting reality has materialized on the transportation scene: our existing air and ground infrastructures will not scale to meet our nation's 21st century demands and expectations for mobility, commerce, safety, and security. The consequence of inaction is diminished quality of life and economic opportunity in the 21st century. Clearly, new thinking is required for transportation that can scale to meet to the realities of a networked, knowledge-based economy in which the value of time is a new coin of the realm. This paper proposes a framework, or topology, for thinking about the problem of scalability of the system of networks that comprise the aviation system. This framework highlights the role of integrated communication-navigation-surveillance systems in enabling scalability of future air transportation networks. Scalability, in this vein, is a goal of the recently formed Joint Planning and Development Office for the Next Generation Air Transportation System. New foundations for 21PstP thinking about air transportation are underpinned by several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems. Complexity science and modern network theory give rise to one of the technological developments of importance. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of scalability, efficiency, robustness, resilience, and other metrics. The paper offers an air transportation system topology as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system architectures, and airspace architectures and procedural concepts. The topology proposed considers air transportation as a system of networks, within which strategies for scalability of the topology may be enabled by technologies and policies. In particular, the effects of scalable ICNS concepts are evaluated within this proposed topology. Alternative business models are appearing on the scene as the old centralized hub-and-spoke model reaches the limits of its scalability. These models include growth of point-to-point scheduled air transportation service (e.g., the RJ phenomenon and the 'Southwest Effect'). Another is a new business model for on-demand, widely distributed, air mobility in jet taxi services. The new businesses forming around this vision are targeting personal air mobility to virtually any of the thousands of origins and destinations throughout suburban, rural, and remote communities and regions. Such advancement in air mobility has many implications for requirements for airports, airspace, and consumers. These new paradigms could support scalable alternatives for the expansion of future air mobility to more consumers in more places.

Holmes, Bruce J.↗

Transportation Network Topologies

A discomforting reality has materialized on the transportation scene: our existing air and ground infrastructures will not scale to meet our nation's 21st century demands and expectations for mobility, commerce, safety, and security. The consequence of inaction is diminished quality of life and economic opportunity in the 21st century. Clearly, new thinking is required for transportation that can scale to meet to the realities of a networked, knowledge-based economy in which the value of time is a new coin of the realm. This paper proposes a framework, or topology, for thinking about the problem of scalability of the system of networks that comprise the aviation system. This framework highlights the role of integrated communication-navigation-surveillance systems in enabling scalability of future air transportation networks. Scalability, in this vein, is a goal of the recently formed Joint Planning and Development Office for the Next Generation Air Transportation System. New foundations for 21st thinking about air transportation are underpinned by several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems. Complexity science and modern network theory give rise to one of the technological developments of importance. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of scalability, efficiency, robustness, resilience, and other metrics. The paper offers an air transportation system topology as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system architectures, and airspace architectures and procedural concepts. The topology proposed considers air transportation as a system of networks, within which strategies for scalability of the topology may be enabled by technologies and policies. In particular, the effects of scalable ICNS concepts are evaluated within this proposed topology. Alternative business models are appearing on the scene as the old centralized hub-and-spoke model reaches the limits of its scalability. These models include growth of point-to-point scheduled air transportation service (e.g., the RJ phenomenon and the Southwest Effect). Another is a new business model for on-demand, widely distributed, air mobility in jet taxi services. The new businesses forming around this vision are targeting personal air mobility to virtually any of the thousands of origins and destinations throughout suburban, rural, and remote communities and regions. Such advancement in air mobility has many implications for requirements for airports, airspace, and consumers. These new paradigms could support scalable alternatives for the expansion of future air mobility to more consumers in more places.

Holmes, Bruce J.↗

TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclones

Tropical cyclones (TCs) are among the most destructive weather systems. Realistically and efficiently detecting and tracking TCs are critical for assessing their impacts and risks. In particular, the eye is a signature feature of a mature TC. Therefore, knowing the eyes’ locations and movements is crucial for both operational weather forecasts and climate risk assessments. Recently, a multilevel robustness framework has been introduced to study the critical points of time-varying vector fields. The framework quantifies the robustness (i.e., structural stability) of critical points across varying neighborhoods. By relating the multilevel robustness with critical point tracking, the framework has demonstrated its potential in cyclone tracking. An advantage is that it identifies cyclonic features using only 2D wind vector fields, which is encouraging as most tracking algorithms require multiple dynamic and thermodynamic variables at different altitudes. A disadvantage is that the framework does not scale well computationally for datasets containing a large number of cyclones. Herein this paper introduces a topologically robust physics-informed tracking framework (TROPHY) for TC tracking. The main idea is to integrate physical knowledge of TC to drastically improve the computational efficiency of multilevel robustness framework for large-scale climate datasets. First, during preprocessing, we propose a physics-informed feature selection strategy to filter 90% of critical points that are short-lived and have low stability, thus preserving good candidates for TC tracking. Second, during in-processing, we impose constraints during the multilevel robustness computation to focus only on physics-informed neighborhoods of TCs. We apply TROPHY to 30 years of 2D wind fields from reanalysis data in ERA5 and generate a number of TC tracks. In comparison with the observed tracks, we demonstrate that TROPHY can capture TC characteristics (e.g., frequency, intensity, duration, latitudes with maximum intensity, and genesis) that are comparable to and sometimes even better than a well-validated TC tracking algorithm that requires multiple dynamic and thermodynamic scalar fields.

97 MATHEMATICS AND COMPUTING↗

Invertible Temper Modeling using Normalizing Flows and the Effects of Structure Preserving Loss

Advanced manufacturing research and development is typically small-scale, owing to costly experiments associated with these novel processes. Deep learning techniques could help accelerate this development cycle but frequently struggle in small-data regimes like the advanced manufacturing space. While prior work has applied deep learning to modeling visually plausible advanced manufacturing microstructures, little work has been done on data-driven modeling of how microstructures are affected by heat treatment, or assessing the degree to which synthetic microstructures are able to support existing workflows. We propose to address this gap by using invertible neural networks (normalizing flows) to model the effects of heat treatment, e.g., tempering. The model is developed using scanning electron microscope imagery from samples produced using shear-assisted processing and extrusion (ShAPE) manufacturing. This approach not only produces visually and topologically plausible samples, but also captures information related to a sample’s material properties or experimental process parameters. We also demonstrate that topological data analysis, used in prior work to characterize microstructures, can also be used to stabilize model training, preserve structure, and improve downstream results. We assess directions for future work and identify our approach as an important step towards end-to-end deep learning system for accelerating advanced manufacturing research and development.

Howland, Sylvia↗

Cyber Attack Sequences Generation for Electric Power Grid

Security assessment of cyber-physical energy systems (CPESs) such as the electric power grid is a critical operation to maintain availability, reliability, and quality of service in the presence of persistent threats from malicious cyber actors. Existing security assessment approaches such as penetration testing and red teaming rely on subject matter expert experience and forensic cyber analysis of historical events to perform realistic, threat-informed assessments of CPES defense. CPESs have a large attack surface because of the heterogeneity and complexity of underlying topology, devices, measurements, and vulnerabilities. The aforementioned approaches lead to partial coverage of the attack surface with a large set of unknown but possible exploits. There is a need to automate the CPES attack surface discovery and contextualize it for relevant, highly probable, real-world attack scenarios. We propose a methodology and framework to facilitate the discovery of the CPES attack surface. We present a multilayer attack graph with ranked attack sequences to describe CPES failure scenarios. We present a work-in-progress framework that lists key components to automate the attack modeling and sequence generation. We demonstrate the published National Electric Sector Cybersecurity Organization Resource CPES failure scenario to highlight the trustworthiness of generated attack sequences.

Dutta, Ashutosh↗

Transformations in Air Transportation Systems For the 21st Century

Globally, our transportation systems face increasingly discomforting realities: certain of the legacy air and ground infrastructures of the 20th century will not satisfy our 21st century mobility needs. The consequence of inaction is diminished quality of life and economic opportunity for those nations unable to transform from the 20th to 21st century systems. Clearly, new thinking is required regarding business models that cater to consumers value of time, airspace architectures that enable those new business models, and technology strategies for innovating at the system-of-networks level. This lecture proposes a structured way of thinking about transformation from the legacy systems of the 20th century toward new systems for the 21st century. The comparison and contrast between the legacy systems of the 20th century and the transformed systems of the 21st century provides insights into the structure of transformation of air transportation. Where the legacy systems tend to be analog (versus digital), centralized (versus distributed), and scheduled (versus on-demand) for example, transformed 21st century systems become capable of scalability through technological, business, and policy innovations. Where air mobility in our legacy systems of the 20th century brought economic opportunity and quality of life to large service markets, transformed air mobility of the 21st century becomes more equitable available to ever-thinner and widely distributed populations. Several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems create new foundations for 21st thinking about air transportation. One of the technological developments of importance arises from complexity science and modern network theory. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of robustness, resilience, and other metrics. The lecture offers an air transportation system topology and a scale-free network linkage graphic as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system topologies, and airspace architectures and procedural concepts. These new paradigms could support scalable alternatives for the expansion of future air mobility to more consumers in more parts of the world.

Holmes, Bruce J.↗

First-Principles Assessment of ZnTe and CdSe as Prospective Tunnel Barriers at the InAs/Al Interface

Majorana zero modes are predicted to emerge in semiconductor/ superconductor interfaces, such as InAs/Al. Majorana modes could be utilized for fault tolerant topological qubits. However, their realization is hindered by materials challenges. The coupling between the superconductor and the semiconductor may be too strong for Majorana modes to emerge, due to effective doping of the semiconductor by the metallic contact. This could be mediated by adding a tunnel barrier of controlled thickness. We use density functional theory (DFT) with Hubbard U corrections, whose values are machine-learned via Bayesian optimization (BO), to assess ZnTe and CdSe as prospective tunnel barriers for the InAs/Al interface. The results of DFT +U(BO) for ZnTe are validated by comparison to angle resolved photoemission spectroscopy (ARPES). We then study bilayer interfaces of the three semiconductors with each other and with Al, as well as trilayer interfaces with a varying number of ZnTe or CdSe layers inserted between InAs and Al. We find that 16 atomic layers of either material completely insulate the InAs from metal induced gap states (MIGS). However, ZnTe and CdSe differ significantly in their band alignment, such that ZnTe forms an effective barrier for electrons, whereas CdSe forms a barrier for holes. Because of Fermi level pinning in the conduction band at the interface, only electron transport is relevant for InAs-based Majorana devices. Therefore, ZnTe is the better choice. Based on the results of our simulations, we suggest conducting experiments with ZnTe barriers in the thickness range of 6–18 atomic layers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stochastic symplectic reduced-order modeling for model-form uncertainty quantification in molecular dynamics simulations in various statistical ensembles

Here, this work focuses on the representation of model-form uncertainties in molecular dynamics simulations in various statistical ensembles. In prior contributions, the modeling of such uncertainties was formalized and applied to quantify the impact of, and the error generated by, pair-potential selection in the microcanonical ensemble (NVE). In this work, we extend this formulation and present a linear-subspace reduced-order model for the canonical (NVT) and isobaric (NPT) ensembles. The symplectic reduced-order basis is randomized on the tangent space of the Stiefel manifold to provide topological relationships and capture model-form uncertainty. Using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), we assess the relevance of these stochastic reduced-order atomistic models on canonical problems involving a Lennard-Jones fluid and an argon crystal melt.

42 ENGINEERING↗

Energy storage planning for enhanced resilience of power systems against wildfires and heatwaves

Extreme weather events pose significant risks to power grid stability due to their severe consequences and potential for widespread failures. Energy storage systems hold great potential for enhancing grid resilience against such events by providing reliable power during peak demand periods. However, accurately quantifying the size, location, and investment costs of new energy storage assets is a complex task, as energy storage planning decisions depend on the investment choices of other generation technologies and the integration of new transmission projects. Here, this paper presents a novel capacity expansion planning framework that simultaneously optimizes investments in energy storage, generation, and transmission, determining their optimal size, location, and type, while incorporating extreme weather events into long-term planning. More specifically, our stress-event-informed planning framework integrates the impact of heatwaves and wildfires into the planning process, identifying least-cost investment solutions that comply with policy goals and enhance grid resilience. The proposed framework employs machine-learning-based modeling to project heatwave-induced loads and performance-based risk assessment to evaluate wildfire-driven transmission line derates. Using industry-standard datasets to accurately represent the transmission topology of the Western Interconnection (WI) system, the proposed framework is applied to the WI 40-zone system, with investment decisions reported for the years 2030, 2035, and 2040. Simulation results reveal that with just a 10% increase in investment costs, resilience against extreme events can be significantly improved, with investment decisions heavily favoring energy storage, particularly 4-hour energy storage systems.

25 ENERGY STORAGE↗

Joint Characterization of Vegetation by Satellite Observations from Visible to Microwave Wavelengths - A Sensitivity Analysis

This study presents an evaluation and comparison of visible, near-infrared, passive, and active microwave observations for vegetation characterization on a global basis for a year, with spatial resolution compatible with climatological studies. Visible and near-infrared observations along with the Normalized Difference Vegetation Index come from the Advanced Very High Resolution Radiometer. An atlas of monthly mean microwave land surface emissivities from 19 to 85 GHz has been calculated from the Special Sensor Microwave/Imager for a year, suppressing the atmospheric problems encountered with the use of simple channel combinations. The active microwave measurements are provided by the ERS-1 scatterometer at 5.25 GHz. The capacity to discriminate between vegetation types and to detect the vegetation phenology is assessed in the context of a vegetation classification obtained from in situ observations. A clustering technique derived from the Kohonen topological maps is used to merge the three data sets and interpret their relative variations. NDVI varies with vegetation density but is not very sensitive in semiarid environments and in forested areas. Spurious seasonal cycles and large spatial variability in several areas suggest that atmospheric contamination and/or solar zenith angle drift still affect the NDVI.

NORMALIZED DIFFERENCE VEGETATIVE INDEX↗

Wall-modeled LES of Flow Over a Gaussian Bump

We perform wall-modeled large eddy simulations (WMLES) of turbulent flow over a Gaussian-shaped bump geometry, to assess its performance in the acceleration and separation regions of the flow. An unstructured finite-volume solver is used along with an equilibrium wall model. The Mach number of the oncoming flow selected for the simulation is 0.176, and two Reynolds numbers (Re) are simulated that are about 10000 and 36000 based on boundary layer thickness upstream of the bump. Spanwise periodic results for the lower Re case are compared with the available DNS data, while the full three-dimensional simulation results for the higher Re case are compared to available experimental data. Sensitivity of WMLES results are assessed for a number of factors including grid resolution, wall model exchange location, type of wall model, and unstructured grid topology. The WMLES results for the lower Re case agree well with available DNS data in terms of the wall pressure variation, velocity and turbulent stress profile comparisons. The skin-friction predictions show a reduced tendency to separate. This appears to be accentuated for the higher Re case, for the medium resolution grid used in this study, where WMLES does not predict any flow separation in the mean, which is in contrast to the large separation bubble observed in the experiments.

turbulence↗

MONACO: accurate biological network alignment through optimal neighborhood matching between focal nodes

Motivation: Alignment of protein–protein interaction networks can be used for the unsupervised prediction of functional modules, such as protein complexes and signaling pathways, that are conserved across different species. To date, various algorithms have been proposed for biological network alignment, many of which attempt to incorporate topological similarity between the networks into the alignment process with the goal of constructing accurate and biologically meaningful alignments. Especially, random walk models have been shown to be effective for quantifying the global topological relatedness between nodes that belong to different networks by diffusing node-level similarity along the interaction edges. However, these schemes are not ideal for capturing the local topological similarity between nodes. Results: Here, we propose MONACO, a novel and versatile network alignment algorithm that finds highly accurate pairwise and multiple network alignments through the iterative optimal matching of ‘local’ neighborhoods around focal nodes. Extensive performance assessment based on real networks as well as synthetic networks, for which the ground truth is known, demonstrates that MONACO clearly and consistently outperforms all other state-of-the-art network alignment algorithms that we have tested, in terms of accuracy, coherence and topological quality of the aligned network regions. Furthermore, despite the sharply enhanced alignment accuracy, MONACO remains computationally efficient and it scales well with increasing size and number of networks.

97 MATHEMATICS AND COMPUTING↗

Managing Space Radiation Risks On Lunar and Mars Missions: Risk Assessment and Mitigation

Radiation-induced health risks are a primary concern for human exploration outside the Earth's magnetosphere, and require improved approaches to risk estimation and tools for mitigation including shielding and biological countermeasures. Solar proton events are the major concern for short-term lunar missions (<60 d), and for long-term missions (>60 d) such as Mars exploration, the exposures to the high energy and charge (HZE) ions that make-up the galactic cosmic rays are the major concern. Health risks from radiation exposure are chronic risks including carcinogenesis and degenerative tissue risks, central nervous system effects, and acute risk such as radiation sickness or early lethality. The current estimate is that a more than four-fold uncertainty exists in the projection of lifetime mortality risk from cosmic rays, which severely limits analysis of possible benefits of shielding or biological countermeasure designs. Uncertainties in risk projections are largely due to insufficient knowledge of HZE ion radiobiology, which has led NASA to develop a unique probabilistic approach to radiation protection. We review NASA's approach to radiation risk assessment including its impact on astronaut dose limits and application of the ALARA (As Low as Reasonably Achievable) principle. The recently opened NASA Space Radiation Laboratory (NSRL) provides the capability to simulate the cosmic rays in controlled ground-based experiments with biological and shielding models. We discuss how research at NSRL will lead to reductions in the uncertainties in risk projection models. In developing mission designs, the reduction of health risks and mission constraints including costs are competing concerns that need to be addressed through optimization procedures. Mitigating the risks from space radiation is a multi-factorial problem involving individual factors (age, gender, genetic makeup, and exposure history), operational factors (planetary destination, mission length, and period in the solar cycle), and shielding characteristics (materials, mass, and topology). We review optimization metrics for radiation protection including scenarios that integrate biophysics models of radiation risks, operational variables, and shielding design tools needed to assess exploration mission designs. We discuss the application of a crosscutting metric, based on probabilistic risk assessment, to lunar and Mars mission trade studies including the assessment of multi-factorial problems and the potential benefits of new radiation health research strategies or mitigation technologies.

Cucinotta, F. A.↗