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Program solves physical problems governed by diffusion-type equations, provided that equations can be modeled by lumped-parameter representation. Program is used for thermal analysis, and could be adapted to solve Fourier, Poisson, and Laplace differential equations. Program is in FORTRAN IV and Assembler for execution on UNIVAC 1100-series or CYBER 175.
Algorithms are presented for on-line parameter identification of structural dynamic systems. As an example, they are used to calculate the parameters of a modal model of a flexible beam. The algorithms are tested using hardware consisting of a 12 ft. beam with four voice coil actuators and nine noncontacting displacement sensors. They are programmed in a CDC Cyber 175 digital computer which provides input command signals for the actuators, reads the sensor data, and processes the algorithm to calculate consistent estimates of the modal parameters of the beam. Experimental results are compared with those of simulation analysis.
The capabilities and limitations of the panel aerodynamics (PAN AIR) computer program system are summarized. This program uses a higher order panel method to solve boundary value problems involving the Prandtl-Glauert equation for subsonic and supersonic potential flows. Both aerodynamic and hydrodynamic problems can be solved using this modular software which is written for the CDC 6600 and 7600, and the CYBER 170 series computers.
Errors in files detected and corrected during operation. Permanent File Validation (PFVAL) utility computer program provides CDC CYBER NOS sites with mechanism to verify integrity of permanent file base. Locates and identifies permanent file errors in Mass Storage Table (MST) and Track Reservation Table (TRT), in permanent file catalog entries (PFC's) in permit sectors, and in disk sector linkage. All detected errors written to listing file and system and job day files. Program operates by reading system tables , catalog track, permit sectors, and disk linkage bytes to vaidate expected and actual file linkages. Used extensively to identify and locate errors in permanent files and enable online correction, reducing computer-system downtime.
This paper introduces a novel framework for modeling interacting humans in a multi-stage game environment by combining concepts from game theory and reinforcement learning. The proposed model has the following desirable characteristics: (1) Bounded rational players, (2) strategic (i.e., players account for one anothers reward functions), and (3) is computationally feasible even on moderately large real-world systems. To do this we extend level-K reasoning to policy space to, for the first time, be able to handle multiple time steps. This allows us to decompose the problem into a series of smaller ones where we can apply standard reinforcement learning algorithms. We investigate these ideas in a cyber-battle scenario over a smart power grid and discuss the relationship between the behavior predicted by our model and what one might expect of real human defenders and attackers.
The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is investigating revolutionary and advanced universal, reliable, always available, cyber secure and affordable Communication, Navigation, Surveillance (CNS) options for all altitudes of UAS operations. In Spring 2015, NASA issued a Call for Proposals under NASA Research Announcements (NRA) NNH15ZEA001N, Amendment 7 Subtopic 2.4. Boeing was selected to conduct a study with the objective to determine the most promising candidate technologies for Unmanned Air Systems (UAS) air-to-air and air-to-ground data exchange and analyze their suitability in a post-NextGen NAS environment. The overall objectives are to develop UAS CNS requirements and then develop architectures that satisfy the requirements for UAS in both controlled and uncontrolled air space. This contract is funded under NASAs Aeronautics Research Mission Directorates (ARMD) Aviation Operations and Safety Program (AOSP) Safe Autonomous Systems Operations (SASO) project and proposes technologies for the Unmanned Air Systems Traffic Management (UTM) service. Communications, Navigation and Surveillance (CNS) requirements must be developed in order to establish a CNS architecture supporting Unmanned Air Systems integration in the National Air Space (UAS in the NAS). These requirements must address cybersecurity, future communications, satellite-based navigation APNT, and scalable surveillance and situational awareness. CNS integration, consolidation and miniaturization requirements are also important to support the explosive growth in small UAS deployment. Air Traffic Management (ATM) must also be accommodated to support critical Command and Control (C2) for Air Traffic Controllers (ATC). This document therefore presents UAS CNS requirements that will guide the architecture.
This paper involves a numerical simulation of the final stages of transition to turbulence in plane channel flow at a Reynolds number of 1500. Three-dimensional incompressible Navier-Stokes equations are numerically integrated to obtain the time evolution of two- and three-dimensional finite-amplitude disturbances. Computations are performed on the CYBER-203 vector processor for a 32 x 51 x 32 grid. Solutions indicate the existence of structures similar to those observed in the laboratory and characteristics of the various stages of transition that lead to final breakdown. In particular, evidence points to the formation of a upside-down-V-shaped vortex and the subsequent system of horseshoe vortices inclined to the main flow direction as the primary elements of transition. Details of the resulting flow field after breakdown indicate the evolution of streaklike formations found in turbulent flows. Although the flow field does approach a steady state (turbulent channel flow), the introduction of subgrid-scale terms seems necessary to obtain fully developed turbulence statistics.
Small unmanned aircraft systems (UASs) are expected to take major roles in future smart cities, for example, by delivering goods and merchandise, potentially serving as mobile hot spots for broadband wireless access, and maintaining surveillance and security. Although they can be used for the betterment of the society, they can also be used by malicious entities to conduct physical and cyber attacks to infrastructure, private/public property, and people. Even for legitimate use-cases of small UASs, air traffic management (ATM) for UASs becomes of critical importance for maintaining safe and collusion-free operation. Therefore, various ways to detect, track, and interdict potentially unauthorized drones carries critical importance for surveillance and ATM applications. In this paper, we will review techniques that rely on ambient radio frequency signals (emitted from UASs), radars, acoustic sensors, and computer vision techniques for detection of malicious UASs. We will present some early experimental and simulation results on radar-based range estimation of UASs, and receding horizon tracking of UASs. Subsequently, we will overview common techniques that are considered for interdiction of UASs.
In this paper, we elaborate on the key actors within the context of the cyber world at the Jet Propulsion Laboratory and use Bayesian Belief Networks to represent the causal and probabilistic relationships between the various elements that affect an actor and the likelihood of exploits and adverse consequences that can occur due to an exploit. We assess the effectiveness of each of the mitigative methods and the sensitivity of the system to each of the aggravating as well as mitigative factors. We use a combination of objective incident data and Subject Matter Expert knowledge as input to these models.
STABCAR can be used to determine the characteristic roots of flexible, actively controlled aircraft, including the effects of unsteady aerodynamics. A modal formulation and a transfer-matrix representation of the control system are employed. Operable in either a batch or an interactive mode, STABCAR can provide graphical or tabular output of the variation of the roots with velocity, density, altitude, dynamic pressure or feedback gains. Herein the mathematical model, program structure, input requirements, output capabilities, and a series of sample cases are detailed. STABCAR was written for use on CDC CYBER 175 equipment; modification would be required for operation on other machines.
The Network Generation Program (NETGEN), which creates logic networks from task chart data is presented. NETGEN is written in CDC FORTRAN IV (Extended) and runs in a batch mode on the CDC 6000 and CYBER 170 series computers. Data is input via a two-card format and contains information regarding the specific tasks in a project. From this data, NETGEN constructs a logic network of related activities with each activity having unique predecessor and successor nodes, activity duration, descriptions, etc. NETGEN then prepares this data on two files that can be used in the Project Planning Analysis and Reporting System Batch Network Scheduling program and the EZPERT graphics program.
A three-dimensional elliptic solver technique is utilized to generate surface-fitted coordinates about wing/wing-tip configurations. The method is applicable to wings of arbitrary section profile and camber, leading-edge sweep, taper ratio, and spanwise thickness variation. The basic theory of three-dimensional elliptic mappings is developed along with a method to compute interior coordinate control functions. Examples of grids generated about several wing/wing-tip geometries are given. A 49 x 33 x 17 grid requires about 3 minutes of CPU time on a CYBER 203 computer.
Social computing has the potential to contribute to scientific research. Ongoing developments in information and communications technology improve capabilities for enabling scientific research, including research fostered by social computing capabilities. The recent emergence of e-Science practices has demonstrated the benefits from improvements in the technological infrastructure, or cyber-infrastructure, that has been developed to support science. Cloud computing is one example of this e-Science trend. Our own work in the area of software reuse offers methods that can be used to improve new technological development, including cloud computing capabilities, to support scientific research practices. In this paper, we focus on software reuse and its potential to contribute to the development and evaluation of information systems and related services designed to support new capabilities for conducting scientific research.
Very efficient algorithms for solving large sparse systems of simultaneous linear equations have been developed for serial processing computers. These involve a reordering of matrix rows and columns in order to obtain a near triangular pattern of nonzero elements. Then an LU factorization is developed to represent the matrix inverse in terms of a sequence of elementary Gaussian eliminations, or pivots. In this paper it is shown how these algorithms are adapted for efficient implementation on vector processors. Results obtained on the CYBER 200 Model 205 are presented for a series of large test problems which show the comparative advantages of the triangularization and vector processing algorithms.
Results obtained from a numerical simulation of the final stages of transition to turbulence in plane channel flow are described. Three dimensional, incompressible Navier-Stokes equations are numerically integrated to obtain the time evolution of two and three dimensional finite amplitude disturbances. Computations are performed on CYBER-203 vector processor for a 32x51x32 grid. Results are presented for no-slip boundary conditions at the solid walls as well as for periodic suction blowing to simulate active control of transition by mass transfer. Solutions indicate that the method is capable of simulating the complex character of vorticity dynamics during the various stages of transition and final breakdown. In particular, evidence points to the formation of a lambda-shape vortex and the subsequent system of horseshoe vortices inclined to the main flow direction as the main elements of transition. Calculations involving periodic suction-blowing indicate that interference with a wave of suitable phase and amplitude reduces the disturbance growth rates.
A numerical simulation of the final stages of transition to turbulence in plane channel flow is reported. Three dimensional, incompressible Navier-Stokes equations are numerically integrated to obtain the time-evolution of two and three dimensional finite amplitude disturbances. Computations are performed on the CYBER-203 vector processor for a 32x51x32 grid. Results are presented for no-slip boundary conditions at the solid walls as well as for periodic suction-blowing to simulate active control of transition by mass transfer. Solutions indicate that the method is capable of simulating the complex character of vorticity dynamics during the various stages of transition and final breakdown. In particular, evidence points to the formation of a lambda-shape vortex and the subsequent system of horseshoe vortices inclined to the main flow direction as the main elements of transition. Calculations involving suction-blowing indicate that interference with a wave of suitable phase and amplitude reduces the disturbance growth rates.
NASA and the Aviation Industry is looking into reduced crew operations (RCO) that would cut today's required two-person flight crews down to a single pilot with support from ground-based crews. Shared responsibility across air and ground personnel will require highly reliable and secure data communication and supporting automation, which will be safety-critical for passenger and cargo aircraft. This paper looks at the different types and degrees of authority delegation given from the air to the ground and the ramifications of each, including the safety and security hazards introduced, the mitigation mechanisms for these hazards, and other demands on an RCO system architecture which would be highly invasive into (almost) all safety-critical avionics. The adjacent fields of unmanned aerial systems and autonomous ground vehicles are viewed to find problems that RCO may face and related aviation accident scenarios are described. The paper explores possible data communication architectures to meet stringent performance and information security (INFOSEC) requirements of RCO. Subsequently, potential challenges for RCO data communication authentication, encryption and non-repudiation are identified.
NASA and the Aviation Industry is looking into reduced crew operations (RCO) that would cut today's required two-person flight crews down to a single pilot with support from ground-based crews. Shared responsibility across air and ground personnel will require highly reliable and secure data communication and supporting automation, which will be safety-critical for passenger and cargo aircraft. This paper looks at the different types and degrees of authority delegation given from the air to the ground and the ramifications of each, including the safety and security hazards introduced, the mitigation mechanisms for these hazards, and other demands on an RCO system architecture which would be highly invasive into (almost) all safety-critical avionics. The adjacent fields of unmanned aerial systems and autonomous ground vehicles are viewed to find problems that RCO may face and related aviation accident scenarios are described. The paper explores possible data communication architectures to meet stringent performance and information security (INFOSEC) requirements of RCO. Subsequently, potential challenges for RCO data communication authentication, encryption and non-repudiation are identified. The approach includes a comprehensive safety-hazard analysis of the RCO system to determine top level INFOSEC requirements for RCO and proposes an option for effective RCO implementation. This paper concludes with questioning the economic viability of RCO in light of the expense of overcoming the operational safety and security hazards it would introduce.