The Experts below are selected from a list of 300 Experts worldwide ranked by ideXlab platform
Smith, Andrew N. - One of the best experts on this subject based on the ideXlab platform.
-
Development and Analysis of the Automated Object Reentry Survival Analysis Tool Parametric Study Wrapper
2019Co-Authors: Greene, Benton R., Smith, Andrew N.Abstract:The NASA Orbital Debris Program Office (ODPO) Safety Group at the Johnson Space Center analyzes reentering spacecraft at the end of life. The program primarily used by ODPO in this effort is the Object Reentry Survival Analysis Tool (Orsat). Orsat utilizes shape primitives as well as a variety of other parameters (material, size, thickness, aerodynamic mass, orbit inclination, etc.) to simulate the reentry process and ultimately, to determine if a spacecraft could be hazardous to the population on the ground. The NASA ODPO plans to automate the Orsat process to run multiple Orsat input files either concurrently or consecutively. This type of automation program will provide several benefits. First, there is a need to run large parametric studies for Orsat analysts to gain a greater understanding of reentering objects sensitivity to certain input variables. Secondly, a database of pre-run Orsat cases will be used to develop a survivability model, which could be made available to spacecraft developers as a design for demise (D4D) tool. The recently completed Automated Object Reentry Survival Analysis Tool (AutoOrsat) Wrapper is currently being used to build a survivability database, the first step in developing a survivability model. Already, the data that AutoOrsat has produced provides a greater understanding of the sensitivity of variables such as the initial temperature of the spacecraft, spacecraft breakup altitude, and the aerodynamic mass of spacecraft
-
Development and Analysis of the Automated Object Reentry Survival Analysis Tool Parametric Study Wrapper
2019Co-Authors: Greene, Benton R., Smith, Andrew N.Abstract:The NASA Orbital Debris Program Office (ODPO) studies all aspects of spacecraft end-of-life and orbital debris measurement, modeling, and mitigation. The reentry safety group within the ODPO uses the Object Reentry Survival Analysis Tool (Orsat) to calculate the casualty risk due to reentry of spacecraft and other types of orbital debris. Orsat models spacecraft as a collection of fragments that break apart from the parent object at a pre-defined breakup altitude. It then calculates the trajectory and aero-heating of these fragments to determine which fragments are completely destroyed and which survive to the ground and pose a risk to human population. Because of the historically high computational cost of these calculations, many simplifying assumptions have been made in the traditional calculation and analysis process used by the ODPO, some of which have been shown by recent research by the ODPO and others to be incorrect. Improvements to the Orsat code and advancements in computer technology have vastly decreased the programs processing time, and have allowed the ODPO to develop a capability for large-scale parametric studies and Monte Carlo reentry simulations that can aid in both the initial spacecraft design and provide more detailed and accurate risk analysis to spacecraft operators
Jacques Van Helden - One of the best experts on this subject based on the ideXlab platform.
-
regulatory sequence analysis tools
Nucleic Acids Research, 2003Co-Authors: Jacques Van HeldenAbstract:The web resource Regulatory Sequence Analysis Tools (RSAT) (http://rsat.ulb.ac.be/rsat) offers a collection of software tools dedicated to the prediction of regulatory sites in non-coding DNA sequences. These tools include sequence retrieval, pattern discovery, pattern matching, genome-scale pattern matching, feature-map drawing, random sequence generation and other utilities. Alternative formats are supported for the representation of regulatory motifs (strings or position-specific scoring matrices) and several algorithms are proposed for pattern discovery. RSAT currently holds >100 fully sequenced genomes and these data are regularly updated from GenBank.
Andrea Montanari - One of the best experts on this subject based on the ideXlab platform.
-
the set of solutions of random xOrsat formulae
Symposium on Discrete Algorithms, 2012Co-Authors: Morteza Ibrahimi, Yash Kanoria, Matt Kraning, Andrea MontanariAbstract:The XOR-satisfiability (XOrsat) problem requires finding an assignment of n Boolean variables that satisfy m exclusive OR (XOR) clauses, whereby each clause constrains a subset of the variables. We consider random XOrsat instances, drawn uniformly at random from the ensemble of formulae containing n variables and m clauses of size k. This model presents several structural similarities to other ensembles of constraint satisfaction problems, such as k-satisfiability (k-SAT). For many of these ensembles, as the number of constraints per variable grows, the set of solutions shatters into an exponential number of well-separated components. This phenomenon appears to be related to the difficulty of solving random instances of such problems. We prove a complete characterization of this clustering phase transition for random k-XOrsat. In particular we prove that the clustering threshold is sharp and determine its exact location. We prove that the set of solutions has large conductance below this threshold and that each of the clusters has large conductance above the same threshold. Our proof constructs a very sparse basis for the set of solutions (or the subset within a cluster). This construction is achieved through a low complexity iterative algorithm.
-
the set of solutions of random xOrsat formulae
arXiv: Discrete Mathematics, 2011Co-Authors: Morteza Ibrahimi, Yash Kanoria, Matt Kraning, Andrea MontanariAbstract:The XOR-satisfiability (XOrsat) problem requires finding an assignment of $n$ Boolean variables that satisfy $m$ exclusive OR (XOR) clauses, whereby each clause constrains a subset of the variables. We consider random XOrsat instances, drawn uniformly at random from the ensemble of formulae containing $n$ variables and $m$ clauses of size $k$. This model presents several structural similarities to other ensembles of constraint satisfaction problems, such as $k$-satisfiability ($k$-SAT), hypergraph bicoloring and graph coloring. For many of these ensembles, as the number of constraints per variable grows, the set of solutions shatters into an exponential number of well-separated components. This phenomenon appears to be related to the difficulty of solving random instances of such problems. We prove a complete characterization of this clustering phase transition for random $k$-XOrsat. In particular, we prove that the clustering threshold is sharp and determine its exact location. We prove that the set of solutions has large conductance below this threshold and that each of the clusters has large conductance above the same threshold. Our proof constructs a very sparse basis for the set of solutions (or the subset within a cluster). This construction is intimately tied to the construction of specific subgraphs of the hypergraph associated with an instance of $k$-XOrsat. In order to study such subgraphs, we establish novel local weak convergence results for them.
Greene, Benton R. - One of the best experts on this subject based on the ideXlab platform.
-
Development and Analysis of the Automated Object Reentry Survival Analysis Tool Parametric Study Wrapper
2019Co-Authors: Greene, Benton R., Smith, Andrew N.Abstract:The NASA Orbital Debris Program Office (ODPO) Safety Group at the Johnson Space Center analyzes reentering spacecraft at the end of life. The program primarily used by ODPO in this effort is the Object Reentry Survival Analysis Tool (Orsat). Orsat utilizes shape primitives as well as a variety of other parameters (material, size, thickness, aerodynamic mass, orbit inclination, etc.) to simulate the reentry process and ultimately, to determine if a spacecraft could be hazardous to the population on the ground. The NASA ODPO plans to automate the Orsat process to run multiple Orsat input files either concurrently or consecutively. This type of automation program will provide several benefits. First, there is a need to run large parametric studies for Orsat analysts to gain a greater understanding of reentering objects sensitivity to certain input variables. Secondly, a database of pre-run Orsat cases will be used to develop a survivability model, which could be made available to spacecraft developers as a design for demise (D4D) tool. The recently completed Automated Object Reentry Survival Analysis Tool (AutoOrsat) Wrapper is currently being used to build a survivability database, the first step in developing a survivability model. Already, the data that AutoOrsat has produced provides a greater understanding of the sensitivity of variables such as the initial temperature of the spacecraft, spacecraft breakup altitude, and the aerodynamic mass of spacecraft
-
Development and Analysis of the Automated Object Reentry Survival Analysis Tool Parametric Study Wrapper
2019Co-Authors: Greene, Benton R., Smith, Andrew N.Abstract:The NASA Orbital Debris Program Office (ODPO) studies all aspects of spacecraft end-of-life and orbital debris measurement, modeling, and mitigation. The reentry safety group within the ODPO uses the Object Reentry Survival Analysis Tool (Orsat) to calculate the casualty risk due to reentry of spacecraft and other types of orbital debris. Orsat models spacecraft as a collection of fragments that break apart from the parent object at a pre-defined breakup altitude. It then calculates the trajectory and aero-heating of these fragments to determine which fragments are completely destroyed and which survive to the ground and pose a risk to human population. Because of the historically high computational cost of these calculations, many simplifying assumptions have been made in the traditional calculation and analysis process used by the ODPO, some of which have been shown by recent research by the ODPO and others to be incorrect. Improvements to the Orsat code and advancements in computer technology have vastly decreased the programs processing time, and have allowed the ODPO to develop a capability for large-scale parametric studies and Monte Carlo reentry simulations that can aid in both the initial spacecraft design and provide more detailed and accurate risk analysis to spacecraft operators
Morteza Ibrahimi - One of the best experts on this subject based on the ideXlab platform.
-
the set of solutions of random xOrsat formulae
Symposium on Discrete Algorithms, 2012Co-Authors: Morteza Ibrahimi, Yash Kanoria, Matt Kraning, Andrea MontanariAbstract:The XOR-satisfiability (XOrsat) problem requires finding an assignment of n Boolean variables that satisfy m exclusive OR (XOR) clauses, whereby each clause constrains a subset of the variables. We consider random XOrsat instances, drawn uniformly at random from the ensemble of formulae containing n variables and m clauses of size k. This model presents several structural similarities to other ensembles of constraint satisfaction problems, such as k-satisfiability (k-SAT). For many of these ensembles, as the number of constraints per variable grows, the set of solutions shatters into an exponential number of well-separated components. This phenomenon appears to be related to the difficulty of solving random instances of such problems. We prove a complete characterization of this clustering phase transition for random k-XOrsat. In particular we prove that the clustering threshold is sharp and determine its exact location. We prove that the set of solutions has large conductance below this threshold and that each of the clusters has large conductance above the same threshold. Our proof constructs a very sparse basis for the set of solutions (or the subset within a cluster). This construction is achieved through a low complexity iterative algorithm.
-
the set of solutions of random xOrsat formulae
arXiv: Discrete Mathematics, 2011Co-Authors: Morteza Ibrahimi, Yash Kanoria, Matt Kraning, Andrea MontanariAbstract:The XOR-satisfiability (XOrsat) problem requires finding an assignment of $n$ Boolean variables that satisfy $m$ exclusive OR (XOR) clauses, whereby each clause constrains a subset of the variables. We consider random XOrsat instances, drawn uniformly at random from the ensemble of formulae containing $n$ variables and $m$ clauses of size $k$. This model presents several structural similarities to other ensembles of constraint satisfaction problems, such as $k$-satisfiability ($k$-SAT), hypergraph bicoloring and graph coloring. For many of these ensembles, as the number of constraints per variable grows, the set of solutions shatters into an exponential number of well-separated components. This phenomenon appears to be related to the difficulty of solving random instances of such problems. We prove a complete characterization of this clustering phase transition for random $k$-XOrsat. In particular, we prove that the clustering threshold is sharp and determine its exact location. We prove that the set of solutions has large conductance below this threshold and that each of the clusters has large conductance above the same threshold. Our proof constructs a very sparse basis for the set of solutions (or the subset within a cluster). This construction is intimately tied to the construction of specific subgraphs of the hypergraph associated with an instance of $k$-XOrsat. In order to study such subgraphs, we establish novel local weak convergence results for them.