Recent Activities of the Marshall Space Flight Center Natural Environments Branch Terrestrial & Planetary Environments Team
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Nathan Curtis↗
SEARCH · Engineering Papers
Results for “environment”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Cactus Environment Machine: Shared Environment Call-by-Need.
Abstract not provided.
Stelle, George Widgery↗
Cactus Environment Machine: Shared Environment Call-by-Need.
Abstract not provided.
Stelle, George Widgery↗
Methods to Envelope Multiple Random Vibration Environments into a Single MIMO Environment
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Mayes, Randall Lee [Sandia National Laboratories (↗
SLS-SPEC-159 Cross-Program Design Specification for Natural Environments (DSNE) Revision D
This document is derived from the former National Aeronautics and Space Administration (NASA) Constellation Program (CxP) document CxP 70023, titled "The Design Specification for Natural Environments (DSNE), Revision C." The original document has been modified to represent updated Design Reference Missions (DRMs) for the NASA Exploration Systems Development (ESD) Programs. The DSNE completes environment-related specifications for architecture, system-level, and lower-tier documents by specifying the ranges of environmental conditions that must be accounted for by NASA ESD Programs. To assure clarity and consistency, and to prevent requirements documents from becoming cluttered with extensive amounts of technical material, natural environment specifications have been compiled into this document. The intent is to keep a unified specification for natural environments that each Program calls out for appropriate application. This document defines the natural environments parameter limits (maximum and minimum values, energy spectra, or precise model inputs, assumptions, model options, etc.), for all ESD Programs. These environments are developed by the NASA Marshall Space Flight Center (MSFC) Natural Environments Branch (MSFC organization code: EV44). Many of the parameter limits are based on experience with previous programs, such as the Space Shuttle Program. The parameter limits contain no margin and are meant to be evaluated individually to ensure they are reasonable (i.e., do not apply unrealistic extreme-on-extreme conditions). The natural environments specifications in this document should be accounted for by robust design of the flight vehicle and support systems. However, it is understood that in some cases the Programs will find it more effective to account for portions of the environment ranges by operational mitigation or acceptance of risk in accordance with an appropriate program risk management plan and/or hazard analysis process. The DSNE is not intended as a definition of operational models or operational constraints, nor is it adequate, alone, for ground facilities which may have additional requirements (for example, building codes and local environmental constraints). "Natural environments," as the term is used here, refers to the environments that are not the result of intended human activity or intervention. It consists of a variety of external environmental factors (most of natural origin and a few of human origin) which impose restrictions or otherwise impact the development or operation of flight vehicles and destination surface systems. These natural environments include the following types of environments: Terrestrial environments at launch, abort, and normal landing sites (winds, temperatures, pressures, surface roughness, sea conditions, etc.); Space environments (ionizing radiation, orbital debris, meteoroids, thermosphere density, plasma, solar, Earth, and lunar-emitted thermal radiation, etc.); Destination environments (Lunar surface and orbital, Mars atmosphere and surface, near Earth asteroids, etc.). Many of the environmental specifications in this document are based on models, data, and environment descriptions contained in the CxP 70044, Constellation Program Natural Environment Definition for Design (NEDD). The NEDD provides additional detailed environment data and model descriptions to support analytical studies for ESD Programs. For background information on specific environments and their effects on spacecraft design and operations, the environment models, and the data used to generate the specifications contained in the DSNE, the reader is referred to the NEDD paragraphs listed in each section of the DSNE. Also, most of the environmental specifications in this document are tied specifically to the ESD DRMs in ESD-10012, Revision B, Exploration Systems Development Concept of Operations (ConOps). Coordination between these environment specifications and the DRMs must be maintained. This document should be compatible with the current ESD DRMs, but updates to the mission definitions and variations in interpretation may require adjustments to the environment specifications.
Roberts, Barry C.↗
Assessing Reservoir Depositional Environments to Develop and Quantify Improvements in CO 2 Storage Efficiency. A Reservoir Simulation Approach
The storage potential and fluid movement within formations are dependent on the unique hydraulic characteristics of their respective depositional environments. Storage efficiency (E) quantifies the potential for storage in a geologic depositional environment and is used to assess basinal or regional CO 2 storage resources. Current estimates of storage resources are calculated using common E ranges by lithology and not by depositional environment. The objectives of this project are to quantify E ranges and identify E enhancement strategies for different depositional environments via reservoir simulation studies. The depositional environments considered include deltaic, shelf clastic, shelf carbonate, fluvial deltaic, strandplain, reef, fluvial and alluvial, and turbidite. Strategies considered for enhancing E include CO 2 injection via vertical, horizontal, and deviated wells, selective completions, water production, and multi-well injection. Conceptual geologic and geocellular models of the depositional environments were developed based on data from Illinois Basin oil fields and gas storage sites. The geologic and geocellular models were generalized for use in other US sedimentary basins. An important aspect of this work is the development of conceptual geologic and geocellular models that reflect the uniqueness of each depositional environment. Different injection well completions methods were simulated to investigate methods of enhancing E in the presence of geologic heterogeneity specific to a depositional environment. Modeling scenarios included horizontal wells (length, orientation, and inclination), selective and dynamic completions, water production, and multiwell injection. A Geologic Storage Efficiency Calculator (GSECalc) was developed to calculate E from reservoir simulation output. Estimated E values were normalized to diminish their dependency on fluid relative permeability. Classifying depositional environments according to normalized baseline E ranges ranks fluvial deltaic and turbidite highest and shelf carbonate lowest. The estimated average normalized baseline E of turbidite, and shelf carbonate depositional environments are 42.5% and 13.1%, with corresponding standard deviations of 11.3%, and 3.10%, respectively. Simulations of different plume management techniques suggest that the horizontal well, multi-well injection with brine production from blanket vertical producers are the most efficient E enhancement strategies in seven of eight depositional environments; for the fluvial deltaic depositional environment, vertical well with blanket completions is the most efficient. This study estimates normalized baseline E ranges for eight depositional environments, which can be used to assess the CO 2 storage resource of candidate formations. This study also improves the general understanding of depositional environment’s influence on E. The lessons learned and results obtained from this study can be extrapolated to formations in other US basins with formations of similar depositional environments, which should be used to further refine regional and national storage resource estimates in future editions of the Carbon Utilization and Storage Atlas of the United States. Further study could consider the economic feasibility of the E enhancement strategies identified here.
01 COAL, LIGNITE, AND PEAT↗
Panel Session 82: Shareholder Engagement with DOE Associate Undersecretary's Environment, Health, Safety, and Security
This panel discussed the mission of the US DOE Office of the Associate Under Secretary for the Office of Environment, Health, Safety and Security (AU) and its functional support to the overall mission of the DOE, DOE Office of Environmental Management, and the contractor partners that support that overall mission. Participation in this panel helps achieve one of AU's strategic plan goals - to engage stakeholders to ensure AU's Environment, Health, Safety and Security (EHS and S) policy and support activities align with DOE mission needs. The Panel included stakeholders to discuss their perspectives on AU stakeholder engagement as well as representatives from four policy and support offices from AU. This panel was an important implementation of the DOE Office of the Associate Under Secretary for the Office of EHS and S (AU) strategic plan goals - to engage stakeholders to ensure AUs Environment, Health, Safety and Security (EHS and S) policy and support activities align with DOE mission needs. The panel included stakeholders to discuss their perspectives on AU stakeholder engagement as well as representatives from four policy and support offices from AU including the Office of Health and Safety (AU-10); Office of Environmental Protection and ES and H Reporting (AU-20); Office of Nuclear Safety (AU-30); and Office of Security (AU-50). Presentations proposed include: 1 - Office of Environment, Health, Safety and Security (AU) - Stakeholder Engagement (Matthew Moury, US DOE, Office of Environment, Health, Safety and Security (USA)); 2 - Environment, Health, Safety, and Security Policy Making: Rules, Directives, Technical Standards and Programs (Patricia Worthington, US DOE, Office of Environment, Health, Safety and Security (USA)); 3 - Environment, Health, Safety, and Security: Corporate Programs (Josh Silverman, US DOE, Office of Environment, Health, Safety and Security (USA)); 4 - Environment, Health, Safety and Security: Technical Assistance (Marc Brooks, US DOE, Office of Environment, Health, Safety and Security (USA)); 5 - Environment, Health, Safety and Security: Goals and Initiatives (Tom Hiltz, US DOE, Office of Environment, Health, Safety and Security (USA)); 6 - Shareholder Engagement with DOE Associate Undersecretary's Environment, Health, Safety, and Security (Greg Sosson, US DOE (USA)); 7 - Nuclear Safety Center of Excellence (Chip Lagdon, Bechtel National, Inc (USA)); 8 - EFCOG Safety Working Group (Jan Preston, Fluor Corporation (USA))
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Design and "As Flown" Radiation Environments for Materials in Low Earth Orbit
A conservative design approach was adopted by the International Space Station Program for specifying total ionizing radiation dose requirements for use in selecting and qualifying materials for construction of the International Space Station. The total ionizing dose design environment included in SSP 30512 Space Station Ionizing Radiation Design Environment is based on trapped proton and electron fluence derived from the solar maximum versions of the AE-8 and AP-8 models, respectively, specified for a circular orbit at 500 km altitude and 51.7 degree inclination. Since launch, the range of altitudes utilized for Space Station operations vary from a minimum of approximately 330 km to a maximum of approximately 405 km with a mean operational altitude less than 400 km. The design environment, therefore, overestimates the radiation environment because the particle flux in the South Atlantic Anomaly is the primary contributor to radiation dose in low Earth orbit and flux within the Anomaly is altitude dependent. In addition, a 2X multiplier is often applied to the design environment to cover effects from the contributions of galactic cosmic rays, solar energetic particle events, geomagnetic storms, and uncertainties in the trapped radiation models which are not explicitly included in the design environment. Application of this environment may give radiation dose overestimates on the order of 1OX to 30X for materials exposed to the space environment, suggesting that materials originally qualified for ten year exposures on orbit may be used for longer periods without replacement. In this paper we evaluate the "as flown" radiation environments derived from historical records of the ISS flight trajectory since launch and compare the results with the SSP 30512 design environment to document the magnitude of the radiation dose overestimate provided by the design environment. "As flown" environments are obtained from application of the AE-8/AP-8 trapped particle models along the ISS flight trajectory including variations in altitude due to decay of the vehicle orbit and periodic reboosts to higher altitudes. In addition, an estimate of the AE-8 model to predict low Earth orbit electron flux (because the radiation dose for thin materials is dominated by the electron component of the radiation environment) is presented based on comparisons of the AE-8 model to measurements of electron integral flux at approximately 850 km from the Medium Energy Proton and Electron Detector on board the NOAA Polar Operational Environmental Satellite.
Minow, Joseph↗
Space Environments and Spacecraft Effects Concept: Transitioning Research to Operations and Applications
The National Aeronautics and Space Administration (NASA) is embarking on a course to expand human presence beyond Low Earth Orbit (LEO) while expanding its mission to explore the solar system. Destinations such as Near Earth Asteroids (NEA), Mars and its moons, and the outer planets are but a few of the mission targets. NASA has established numerous organizations specializing in specific space environments disciplines that will serve to enable these missions. To complement these existing discipline organizations, a concept is presented focusing on the development of a space environment and spacecraft effects organization. This includes space climate, space weather, natural and induced space environments, and effects on spacecraft materials and systems. This space environment and spacecraft effects organization would be comprised of Technical Working Groups (TWG) focusing on, for example: a) Charged Particles (CP), b) Space Environmental Effects (SEE), and c) Interplanetary and Extraterrestrial Environments (IEE). These technical working groups will generate products and provide knowledge supporting four functional areas: design environments, environment effects, operational support, and programmatic support. The four functional areas align with phases in the program mission lifecycle and are briefly described below. Design environments are used primarily in the mission concept and design phases of a program. Environment effects focuses on the material, component, sub-system and system-level selection and the testing to verify design and operational performance. Operational support provides products based on real time or near real time space weather observations to mission operators to aid in real time and near-term decision-making. The programmatic support function maintains an interface with the numerous programs within NASA and other federal agencies to ensure that communications are well established and the needs of the programs are being met. The programmatic support function also includes working in coordination with the program in anomaly resolution and generation of lesson learned documentation. The goal of this space environment and spacecraft effects organization is to develop decision-making tools and engineering products to support the mission phases of mission concept through operations by focusing on transitioning research to application. Products generated by this space environments and spacecraft effects organization are suitable for use in anomaly investigations. This paper will describe the organizational structure for this space environments and spacecraft effects organization, and outline the scope of conceptual TWG's and their relationship to the functional areas.
Edwards, D. L.↗
An Overview of the Space Environments and Spacecraft Effects Organization Concept
The National Aeronautics and Space Administration (NASA) is embarking on a course to expand human presence beyond Low Earth Orbit (LEO) while also expanding its mission to explore our Earth, and the solar system. Destinations such as Near Earth Asteroids (NEA), Mars and its moons, and the outer planets are but a few of the mission targets. Each new destination presents an opportunity to increase our knowledge on the solar system and the unique environments for each mission target. NASA has multiple technical and science discipline areas specializing in specific space environments fields that will serve to enable these missions. To complement these existing discipline areas, a concept is presented focusing on the development of a space environment and spacecraft effects (SESE) organization. This SESE organization includes disciplines such as space climate, space weather, natural and induced space environments, effects on spacecraft materials and systems, and the transition of research information into application. This space environment and spacecraft effects organization will be composed of Technical Working Groups (TWG). These technical working groups will survey customers and users, generate products, and provide knowledge supporting four functional areas: design environments, engineering effects, operational support, and programmatic support. The four functional areas align with phases in the program mission lifecycle and are briefly described below. Design environments are used primarily in the mission concept and design phases of a program. Environment effects focuses on the material, component, sub-system, and system-level response to the space environment and include the selection and testing to verify design and operational performance. Operational support provides products based on real time or near real time space weather to mission operators to aid in real time and near-term decision-making. The programmatic support function maintains an interface with the numerous programs within NASA, other federal government agencies, and the commercial sector to ensure that communications are well established and the needs of the programs are being met. The programmatic support function also includes working in coordination with the program in anomaly resolution and generation of lessons learned documentation. The goal of this space environment and spacecraft effects organization is to develop decision-making tools and engineering products to support all mission phases from mission concept through operations by focusing on transitioning research to application. Products generated by this space environments and effects application are suitable for use in anomaly investigations. This paper will describe the scope and purpose of the space environments and spacecraft effects organization and describe the TWG's and their relationship to the functional areas.
Edwards, David L.↗
Environment and initial state engineered dynamics of quantum and classical correlations
Based on an open exactly solvable system coupled to an environment with nontrivial spectral density, we connect the features of quantum and classical correlations with some features of the environment, initial states of the system, and the presence of initial system–environment correlations. Some interesting features not revealed before are observed by changing the structure of environment, the initial states of system, and the presence of initial system–environment correlations. The main results are as follows. (1) Quantum correlations exhibit temporary freezing and permanent freezing even at high temperature of the environment, for which the necessary and sufficient conditions are given by three propositions. (2) Quantum correlations display a transition from temporary freezing to permanent freezing by changing the structure of environment. (3) Quantum correlations can be enhanced all the time, for which the condition is put forward. (4) The one-to-one dependency relationship between all kinds of dynamic behaviors of quantum correlations and the initial states of the system as well as environment structure is established. (5) In the presence of initial system–environment correlations, quantum correlations under local environment exhibit temporary multi-freezing phenomenon. While under global environment they oscillate, revive, and damp, an explanation for which is given. - Highlights: • Various interesting behaviors of quantum and classical correlations are observed in an open exactly solvable model. • The important effects of the bath structure on quantum and classical correlations are revealed. • The one-to-one correspondence between the type of dynamical behavior of quantum discord and the initial state is given. • Quantum correlations are given in the presence of initial qubits–bath correlations.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Interpreting the International Space Station Microgravity Environment
The International Space Station (ISS) serves as a platform for microgravity research for the foreseeable future. A microgravity environment is one in which the effects of gravity are drastically reduced which then allows physical experiments to be conducted without the overpowering effects of gravity. A physical environment with very low-levels of acceleration and vibration has been accomplished by both the free fall associated with orbital flight and the design of the International Space Station. The International Space Station design has been driven by a long-standing, high-level requirement for a microgravity mode of operation. The Space Acceleration Measurement System has been in operation for nearly four years on the ISS measuring the microgravity environment in support of principal investigators and to characterize the ISS microgravity environment. The Principal Investigator Microgravity Services project functions as a detective to ascertain the source of disturbances seen in the ISS microgravity environment to allow correlation between that environment and experimental data. Payload developers need to predict the microgravity environment that will be imposed upon an experiment and ensure that the science and engineering requirements will be met. The Principal Investigator Microgravity Services project is developing n interactive tool to predict the microgravity environment at science payloads based on user defined operational scenarios. These operations (predictions and post-analyses) allow a researcher to examine the microgravity acceleration levels expected to exist when their experiment is operated and then receive an analysis of the environment which existed during their experiment operations. Presented in this paper will be descriptions of the environment predictive tool and an investigation into a previously unknown disturbance in the ISS microgravity environment.
DeLombard, Richard↗
Spacecraft Environment Interactions
As electronic components have grown smaller in size and power and have increased in complexity, their enhanced sensitivity to the space radiation environment and its effects has become a major source of concern for the spacecraft engineer. As a result, the description of the sources of space radiation, the determination of how that radiation propagates through material, and, ultimately, how radiation affects specific circuit components are primary considerations in the design of modern spacecraft. The objective of this paper will be to address the first 2 aspects of the radiation problem. This will be accomplished by first reviewing the natural and man-made space radiation environments. These environments include both the particulate and, where applicable, the electromagnetic (i.e., photon) environment. As the "ambient" environment is typically only relevant to the outer surface of a space vehicle, it will be necessary to treat the propagation of the external environment through the complex surrounding structures to the point inside the spacecraft where knowledge of the internal radiation environment is required. While it will not be possible to treat in detail all aspects of the problem of the radiation environment within a spacecraft, by dividing the problem into these parts-external environment, propagation, and internal environment-a basis for understanding the practical process of protecting a spacecraft from radiation will be established. The consequences of this environment will be discussed by the other presenters at this seminar.
radiation↗
Assessments of Physiology and Cognition in Hybrid-Reality Environments (APACHE)
NASA is planning to return to the Moon in the mid-2020s as a stepping stone to Mars missions in the 2030s. Spacewalks, or extravehicular activities (EVAs), performed on the Moon and Mars will differ in a variety of ways from those that have been performed in decades past. NASA has identified multiple risks to human health and performance associated with a crewed mission to Mars, especially those associated with exploration EVAs which are expected to be a primary mission activity. Crew may be expected to conduct up to 24 hours of EVA per person per week, where the likelihood of injury and/or mental mistakes are increased compared to ground-based training or current microgravity EVAs and the consequences of which can be catastrophic. Current test environments for exploration EVA research and technology development are large, costly facilities that are limited in their availability or capabilities. Spacesuit testing in a reduced gravity environment such as NASA’s Neutral Buoyancy Laboratory, while a good representation of the crew’s physical workload during exploration EVAs, typically has small datasets and is difficult to integrate physiological sensors or other types of crew performance measures. Meanwhile, scientific field-based testing such as NASA’s Desert Research and Technology Studies offers an operationally relevant environment for exploration EVAs, particularly for cognitive workload, but is also limited by small datasets, lack of a pressurized spacesuit, and obtrusive measures. The limitations of current analogs for exploration EVAs identify a need for a new test environment that can approximate both the physical and cognitive demands associated with exploration EVAs to enable rapid, controlled, and repeatable evaluations of human health and performance risks of exploration missions. In response, the Human Physiology, Performance, Protection, and Operations Laboratory (H-3PO) at NASA Johnson Space Center has developed a hybrid reality exploration EVA analog named the Assessments of Physiology And Cognition in Hybrid-reality Environments (APACHE) to address these limitations using a combination of virtual, physical, and hybrid reality techniques. The APACHE facility resides at NASA Johnson Space Center and serves as a large “sandbox” for EVA research and simulation. At its center is a roughly 15x20ft space surrounded by a 14” tall sandbox partially filled with lunar regolith simulant to emulate the physical feeling of walking on a planetary surface and to allow for simulated geology operations. Nearby, a curved passive treadmill (Skillmill Connect, Technogym, Fairfield, NJ) and an omnidirectional treadmill (Infinadeck, Infinadeck, Rocklin, CA) are included to enable exploration of these large virtual environments while also imposing the physical demands, representative timelines, and cognitive burdens required to navigate and traverse these distances during exploration EVA. A 6DOF motion platform is used to simulate rover operations and supports various human performance evaluations and associated risks. Lastly, APACHE can support two extravehicular (EV) crewmembers working in tandem. A computer workstation is located nearby and also supports an intravehicular (IV) crewmember as part of a full mission simulation. The IV crewmember has direct video and audio communication with the EV crew in VR to provide operational and procedural support. The software used in APACHE was created by the JSC Engineering Directorate, in partnership with Buendea, powered by a custom Unreal Engine 5 (UE5.3, Epic Games) project. APACHE currently utilizes the HTC Vive Pro Eye in a wireless configuration for VR simulations. There are two virtual environments that subjects can explore within APACHE, a Lunar and Martian surface. The virtual Lunar surface was created from LIDAR data of the Lunar South Pole to create roughly 16 sq km of explorable terrain. The virtual Martian surface contains roughly 400 sq km of explorable terrain derived from Mars Reconnaissance Orbiter LIDAR data of the Jezero Crater. The immersion and related cognitive burdens of conducting a planetary EVA is simulated through a series of EVA-relevant tasks performed in the VR environment, using these high-fidelity visual representations. Additionally, APACHE includes biosensor driven informatics, such as real-time heart rate monitoring and/or derived values from model simulations, for active monitoring by the EV crew and added cognitive demand. A “Wizard of Oz” control panel enables test operators to activate contingency events such as simulated spacesuit malfunctions, loss of communications, and/or limited visibility. Embedded performance measures such as accuracy, completeness, and execution time have been developed for various exploration tasks to objectively quantify crew performance during an EVA and compare impacts to performance when different environmental stressors, both physical and cognitive, are added to or removed from the simulation. Additionally, validated cognitive and operational performance measures such as the Digit Symbol Substitution Task have been recreated and embedded in VR for direct and relatively unobtrusive measurement of motor perception. The APACHE environment currently supports multiple research studies at NASA. Examples include the CHAPEA project, a series of simulated year-long missions on Mars by a 4-person crew; and the CO2 Contingency Walk Back Study, an investigation of elevated CO2 exposure on crew performance during a contingency EVA scenario. APACHE also provides a test environment to support the development of the Crew State and Risk Model, which is a collection of individualized, mathematical models of crew physical and cognitive state; and the Personalized EVA Informatics and Decision Support system, an operational tool for flight controllers, and eventually a self-reliant Martian crew, to make biomedically-informed decisions in real-time to optimize the EVA planning and execution with respect to crew health and performance. Some technical challenges associated with developing the APACHE environment, as well as current limitations, include VR limitless natural walking with a hybrid spacesuit simulator, optimizing performance for wireless PC VR streaming while maintaining a high degree of visual fidelity, and the integration of various physiological (metabolic masks) and psychometric (eye tracking) sensors with the VR headset.
Human Performance↗
Dynamic assessment of urban economy-environment-energy system using system dynamics model: A case study in Beijing
Highlights: • We combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. • Beijing is selected as a case study. • Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. • Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Economic development, accompanying with environmental damage and energy depletion, becomes essential nowadays. There is a complicated and comprehensive interaction between economics, environment and energy. Understanding the operating mechanism of Energy-Environment-Economy model (3E) and its key factors is the inherent part in dealing with the issue. In this paper, we combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. Beijing is selected as a case study to verify our SD-GIS model. Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Policy-making insights are given based on our results and analysis.
54 ENVIRONMENTAL SCIENCES↗
Multi-trait multi-environment genomic prediction strategies for Miscanthus sacchariflorus
Genomic selection holds the potential to serve as a strategic tool to enhance the genetic gain of complex traits in Miscanthus breeding programs. The development of improved cultivars requires their assessment for various traits across diverse environments to ensure suitable overall performance. Hence, the multi-trait multi-environment (MTME) genomic prediction (GP) models offer an opportunity to improve selection accuracy. This study aims to evaluate the potential of five GP models: (1) three MTME models including genotype-by-trait-by-environment interaction (G×E×T) and (2) two single-trait multi-environment (STME) models (with and without G×E interaction). A Miscanthus sacchariflorus population comprising 336 genotypes evaluated in three environments and scored for four traits (biomass yield YDY, total culm number TCM, average internode length AIL, and culm node number CNN) was analyzed. The predictive ability of the models was evaluated considering three cross-validation schemes resembling realistic scenarios (CV1: predicting new genotypes, CVP: predicting missing traits in a given environment, and CV2: predicting partially observed genotypes). On average, in all cross-validation schemes compared to the STME the predictive ability of the MTME models was 10% to 70% higher for TCM and AIL. On the other hand, for YDY and CNN, both STME models performed similarly or slightly better (between 5 to 64%) than the MTME models in most environments. While the MTME models were not successful for all traits when compared to their STME counterparts, MTME models improved the prediction of the performance of genotypes that were untested across environments or lacked trait information in a specific environment. Overall, our study suggests that MTME GP models can be implemented in Miscanthus breeding programs to improve the predictive ability of the complex traits, shorten breeding cycles, and accelerate selection decisions.
genomic prediction (GP)↗
The Pan-STARRS1 medium-deep survey: The role of galaxy group environment in the star formation rate versus stellar mass relation and quiescent fraction out to z ∼ 0.8
Using a large optically selected sample of field and group galaxies drawn from the Pan-STARRS1 Medium-Deep Survey (PS1/MDS), we present a detailed analysis of the specific star formation rate (SSFR)—stellar mass (M {sub *}) relation, as well as the quiescent fraction versus M {sub *} relation in different environments. While both the SSFR and the quiescent fraction depend strongly on stellar mass, the environment also plays an important role. Using this large galaxy sample, we confirm that the fraction of quiescent galaxies is strongly dependent on environment at a fixed stellar mass, but that the amplitude and the slope of the star-forming sequence is similar between the field and groups: in other words, the SSFR-density relation at a fixed stellar mass is primarily driven by the change in the star-forming and quiescent fractions between different environments rather than a global suppression in the star formation rate for the star-forming population. However, when we restrict our sample to the cluster-scale environments (M > 10{sup 14} M {sub ☉}), we find a global reduction in the SSFR of the star-forming sequence of 17% at 4σ confidence as opposed to its field counterpart. After removing the stellar mass dependence of the quiescent fraction seen in field galaxies, the excess in the quiescent fraction due to the environment quenching in groups and clusters is found to increase with stellar mass, although deeper and larger data from the full PS1/MDS will be required to draw firm conclusions. We argue that these results are in favor of galaxy mergers to be the primary environment quenching mechanism operating in galaxy groups whereas strangulation is able to reproduce the observed trend in the environment quenching efficiency and stellar mass relation seen in clusters. Our results also suggest that the relative importance between mass quenching and environment quenching depends on stellar mass—the mass quenching plays a dominant role in producing quiescent galaxies for more massive galaxies, while less massive galaxies are quenched mostly through the environmental effect, with the transition mass around 1-2 × 10{sup 10} M {sub ☉} in the group/cluster environment.
79 ASTRONOMY AND ASTROPHYSICS↗