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At least 163 records · Page 9

Analyzing Insider Risk Threat to the Internet of Things (IoT)

Recent technological advancement has created a growing convergence of innovation. From machine learning to ubiquitous computing to wireless networks and automation, the world is seeing new technology increasingly capable of connecting with each other. Devices and systems use open communications networks to interact, process information, and react. This is called the Internet of Things (IoT) and is comprised of physical devices that exchange data over networks, creating revolutionary possibilities. The most common way most people interact with an IoT is through ‘smart home’ products like Amazon’s Alexa, which use microphones, speakers, and phones to control a variety of devices, from lights and thermostats, to cameras, to appliances and vacuum cleaners. But the open nature of IoT networks—necessary for their ability to communicate and operate—also introduces privacy and security concerns. At a personal level, this might mean a hack into a home to steal private information, but when applied in broader industries like healthcare, transportation, manufacturing, or the military, this vulnerability can have serious consequences. As IoT usage and interconnectivity increases, so too does the susceptibility to malicious actors. And the entire system is only as secure as its least secure member. This creates particular risk and vulnerability to radiological material industries, as a competent insider adversary could utilize the IoT to potentially steal or access classified or sensitive information about employees, sites, or systems; or simply sabotage security or maintenance from a more remote—and less secure—device. The IoT relies on a secure network across the entire system, especially in transport which may lack the security of more permanent locations; if one device fails, it can create a ripple effect and an insider threat may seek to exploit that connectivity. While IoT benefits drive increased innovation and usage, there are also vulnerabilities an insider threat could exploit; this risk of an IoT to radiological material must be addressed in any mitigation effort.

Kinney, Justin↗

Learning to Control Advanced Life Support Systems

Advanced life support systems have many interacting processes and limited resources. Controlling and optimizing advanced life support systems presents unique challenges. In particular, advanced life support systems are nonlinear coupled dynamical systems and it is difficult for humans to take all interactions into account to design an effective control strategy. In this project. we developed several reinforcement learning controllers that actively explore the space of possible control strategies, guided by rewards from a user specified long term objective function. We evaluated these controllers using a discrete event simulation of an advanced life support system. This simulation, called BioSim, designed by Nasa scientists David Kortenkamp and Scott Bell has multiple, interacting life support modules including crew, food production, air revitalization, water recovery, solid waste incineration and power. They are implemented in a consumer/producer relationship in which certain modules produce resources that are consumed by other modules. Stores hold resources between modules. Control of this simulation is via adjusting flows of resources between modules and into/out of stores. We developed adaptive algorithms that control the flow of resources in BioSim. Our learning algorithms discovered several ingenious strategies for maximizing mission length by controlling the air and water recycling systems as well as crop planting schedules. By exploiting non-linearities in the overall system dynamics, the learned controllers easily out- performed controllers written by human experts. In sum, we accomplished three goals. We (1) developed foundations for learning models of coupled dynamical systems by active exploration of the state space, (2) developed and tested algorithms that learn to efficiently control air and water recycling processes as well as crop scheduling in Biosim, and (3) developed an understanding of the role machine learning in designing control systems for advanced life support.

Subramanian, Devika↗

Svalbard: A Window for Understanding Temporal/Spatial Aspects of Solar Wind Coupling to the Magnetosphere and Ionosphere

The research facilities on the Svalbard archepelego provide a unique opportunity for observing the temporal and spatial characteristics of the interaction of the solar wind with the magnetosphere-ionosphere system. The first sounding rockets from the SvdRak range at Ny-Alesund have opened a new perspective for separating temporal and spatial effects. Finding a correlation between observations from the rockets and the Wind satellite located nearly 200 R(sub E) upstream in the solar wind that had a lag time less than the advection time forced consideration of tilted phase planes of the interp1anetary electric field. From this it was deduced that the interaction process has to involve high latitude merging, the interplanetary magnetic field (IMF) B(sub Y) bifurcates the cusp relative to the high latitude source regions in the Northern and Southern Hemispheres, IMF B(sub X) controls the interaction time in each hemisphere, and the small convection cell is driven by opposite hemisphere merging. Studies with 4 satellites in the solar wind have shown that the tilt of the phase plane varies on a minute-by-minute basis and change significantly on time scales of tens of minutes. Images of the cusp at 557.7 nm provide a nearly instantaneous picture of the temporal and spatial characteristics of merging at the magnetopause and show that the process can occur at multiple locations. The rate and location vary with time.

Maynard, Nelson C.↗

Processing Digital Imagery Data

Earth Resources Laboratory Applications Software (ELAS) is geobased information system designed for analyzing and processing digital imagery data. ELAS offers user of remotely sensed data wide range of easy to use capabilities in areas of land cover analysis. ELAS system written in FORTRAN and Assembler for batch or interactive processing.

Conner, P. K.↗

Hot hydrogen and oxygen atoms in the upper atmospheres of Venus and Mars

Optical observations of hot atoms in the atmospheres of Venus and Mars are briefly reviewed. A summary of hot hydrogen and oxygen production and loss processes is given. Results of some recent model calculations as well as a number of new results of the hot hydrogen and oxygen populations are presented and their implication in terms of solar wind interaction processes is discussed.

Nagy, Andrew F.↗

Update on Covariance Data Testing Strategy at LANL [Slides]

LANL is working towards an ENDF/B-VIII.0-based Covariance Library, with several key goals and work processes outlined. This includes processing through NJOY’s ERRORR module, identifying and correcting mathematical and physical deficiencies, communicating across pipeline from evaluator to end user, understanding use cases and interpreting results, and releasing to customers. Their testing approach includes interaction, processing, checks (mathematical properties, constraints, and physical bounds), and error propagation.

97 MATHEMATICS AND COMPUTING↗

The JPL Resource Allocation Planning and Scheduling Office (RAPSO) process

The Jet Propulsion Laboratory's Resource Allocation Planning and Scheduling Office is chartered to divide the limited amount of tracking hours of the Deep Space Network amongst the various missions in as equitable allotment as can be achieved. To best deal with this division of assets and time, an interactive process has evolved that promotes discussion with agreement by consensus between all of the customers that use the Deep Space Network (DSN). Aided by a suite of tools, the task of division of asset time is then performed in three stages of granularity. Using this approach, DSN loads are either forecasted or scheduled throughout a moving 10-year window.

RAPSO Resource Allocation Planning and Scheduling ↗

Adaptive control with an expert system based supervisory level

Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up to the use of expert systems for more advanced supervision capabilities.

Sullivan, Gerald A.↗

Towards the Development of Real-Time Normalized Burn Ratio (NBR) and Delta NBR Imagery from GOES-16/17 and S-NPP

Burned landscapes present difficult hydrologic forecasting challenges for National Weather Service Offices. Burned soils and landscapes can be conducive to the development of flash flooding and landslides from heavy precipitation events. The severity of the burn scar can be directly related to the risk for debris flows and flash flooding. Burned Area Reflectance Classification (BARC) map is generated to indicate the degree of burn severity, which is generated initially by high-resolution satellite imagery from sources such as Landsat, and later by labor-intensive efforts conducted at the burn scar by Burned Area Emergency Response (BAER) teams. The challenge for operational meteorologists is that these sources of information are not readily available in near real-time. Landsat imagery, for example, may only be available about once every eight days, and cloudy conditions can obstruct the observation of the burn scar during a single pass. BAER teams cannot conduct assessments until the wildfire has been at least 40 percent contained (up to 80 percent in some regions), and the process itself can take further days to weeks to complete depending on a number of factors. To help remedy this lapse in knowledge, NASA SPoRT has developed the generation of NBR imagery in the Advanced Weather Interactive Processing System (AWIPS) using data from the operational GOES 16 and 17 satellites and S-NPP. This presentation will discuss the development of the GOES- and SNPP-derived NBR and dNBR imagery and their initial evaluation by real-time decision makers.

Berndt, Emily↗

Dynamic beam shaping—Improving laser materials processing via feature synchronous energy coupling

Today, tailored laser beams are rarely used and thus an opportunity to optimize existing or introduce new processes is missed. New methods of dynamic beam shaping have the potential to change that in future. This keynote paper deals with methods allowing a transient energy input into the workpiece at such time scales that the underlying interaction processes are guided towards the desired result. It shows principles, categorizes necessary system technology, and gives application examples to familiarize the reader with the topic. It postulates that time-scale-dependent coupling between transient energy input and addressed process features is key for achieving the optimum.

36 MATERIALS SCIENCE↗

Ocean-ice interaction in the marginal ice zone using synthetic aperture radar imagery

Ocean-ice interaction processes in the marginal ice zone (MIZ) by wind, waves, and mesoscale features, such as up/downwelling and eddies are studied using Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) images and an ocean-ice interaction model. A sequence of seven SAR images of the MIZ in the Chukchi Sea with 3 or 6 days interval are investigated for ice edge advance/retreat. Simultaneous current measurements from the northeast Chukchi Sea, as well as the Barrow wind record, are used to interpret the MIZ dynamics. SAR spectra of waves in ice and ocean waves in the Bering and Chukchi Sea are compared for the study of wave propagation and dominant SAR imaging mechanism. By using the SAR-observed ice edge configuration and wind and wave field in the Chukchi Sea as inputs, a numerical simulation has been performed with the ocean-ice interaction model. After 3 days of wind and wave forcing the resulting ice edge configuration, eddy formation, and flow velocity field are shown to be consistent with SAR observations.

Liu, Antony K.↗

Analysis of the Magneto-Hydrodynamic (MHD) Energy Bypass Engine for High-Speed Air-Breathing Propulsion

The performance of the MHD energy bypass air-breathing engine for high-speed propulsion is analyzed in this investigation. This engine is a specific type of the general class of inverse cycle engines. In this paper, the general relationship between engine performance (specific impulse and specific thrust) and the overall total pressure ratio through an engine (from inlet plane to exit plane) is first developed and illustrated. Engines with large total pressure decreases, regardless of cause or source, are seen to have exponentially decreasing performance. The ideal inverse cycle engine (of which the MHD engine is a sub-set) is then demonstrated to have a significant total pressure decrease across the engine; this total pressure decrease is cycle-driven, degrades rapidly with energy bypass ratio, and is independent of any irreversibility. The ideal MHD engine (inverse cycle engine with no irreversibility other than that inherent in the MHD work interaction processes) is next examined and is seen to have an additional large total pressure decrease due to MHD-generated irreversibility in the decelerator and the accelerator. This irreversibility mainly occurs in the deceleration process. Both inherent total pressure losses (inverse cycle and MHD irreversibility) result in a significant narrowing of the performance capability of the MHD bypass engine. The fundamental characteristics of MHD flow acceleration and flow deceleration from the standpoint of irreversibility and second-law constraints are next examined in order to clarify issues regarding flow losses and parameter selection in the MM modules. Severe constraints are seen to exist in the decelerator in terms of allowable deceleration Mach numbers and volumetric (length) required for meaningful energy bypass (work interaction). Considerable difficulties are also encountered and discussed due to thermal/work choking phenomena associated with the deceleration process. Lastly, full engine simulations utilizing inlet shock systems, finite-rate chemistry, wall cooling with thermally balanced engine (fuel heat sink), fuel injection and mixing, friction, etc. are shown and discussed for both the MHD engine and the conventional scramjet. The MHD bypass engine has significantly lower performance in all categories across the Mach number range (8 to 12.2). The lower performance is attributed to the combined effects of 1) additional irreversibility and cooling requirements associated with the MHD components and 2) the total pressure decrease associated with the inverse cycle itself.

Riggins, David W.↗

Soil Organic Matter Dynamics in the Critical Zone

Soil is the thin, vital layer of Earth’s surface that forms the foundation of the Critical Zone and sustains life. This chapter explores the intricate dynamics of soil organic matter within the critical zone, focusing on three key thematic areas: deep soil organic matter, wildfire organic matter interactions, and organic matter erosion. Soil organic matter, although a small fraction of soil mass, plays a crucial role in soil function and ecosystem stability. The complexity of soil organic matter arises from its diverse chemical composition and interactions with minerals, which influence its persistence in the environment. This chapter begins by examining deep soil organic matter, which constitutes a significant portion of global carbon storage. We discuss how deep soil organic matter, typically isolated from surface processes, may become vulnerable to decomposition and carbon release due to disturbances. Next, we explore the impacts of fire on soil organic matter, particularly the formation and stability of pyrolyzed organic matter. The decomposition of pyrolyzer organic matter is influenced by its chemical composition and the surrounding environmental conditions, with implications for carbon cycling and soil fertility in post-fire ecosystems. Finally, the chapter addresses the role of erosion in soil organic matter dynamics. Erosion, accelerated by human activities, redistributes soil organic matter across landscapes, affecting its turnover and the broader biogeochemical cycles. We consider how micro-topographic features and erosion processes interact to influence soil OM stability and carbon sequestration. By synthesizing recent advances in these areas, this chapter provides a comprehensive overview of the complex and dynamic nature of soil organic matter in the critical zone, highlighting its importance in understanding the critical zone in the face of environmental change.

Moreland, Kimber↗

Calculation of helicopter rotor blade/vortex interaction by Navier-Stokes procedures

Interactions of a modern rotor blade with concentrated tip vortices from the previous blades can have a significant influence on the airloads and the aeroacoustics of a helicopter. A better understanding of the blade/vortex interaction process and a method of analyzing its flow field would provide valuable help in the design of helicopters. The work discussed herein represents an initial effort in applying a 3-D, time-dependent Navier-Stokes simulation to the blade vortex interaction problem. The numerical approach is the Linearized Block Implicit (LBI) technique. In this initial effort, consideration is given to the interaction of a wing of idealized geometry and a vortex whose axis is aligned at an arbitrary angle to the wing. The calculations are made for laminar, subsonic flow, and show the time dependent pressure distribution and flow fields resulting from the interaction.

Kim, Y.-N.↗

The President's Day cyclone 17-19 February 1979: An analysis of jet streak interactions prior to cyclogenesis

The President's Day cyclone, produced record breaking snowfall along the East Coast of the United States in February 1979. Conventional radiosonde data, SMS GOES infrared imagery and LFM 2 model diagnostics were used to analyze the interaction of upper and lower tropospheric jet streaks prior to cyclogenesis. The analysis reveals that a series of complex scale interactive processes is responsible for the development of the intense cyclone. The evolution of the subsynoptic scale mass and momentum fields prior to and during the period of rapid development of the President's Day cyclone utilizing conventional data and SMS GOES imagery is documented. The interaction between upper and lower tropospheric jet streaks which occurred prior to the onset of cyclogenesis is discussed as well as the possible effects of terrain modified airflow within the precyclogenesis environment. Possible deficiencies in the LFM-2 initial wind fields that could have been responsible, in part, for the poor numerical forecast are examined.

Uccellini, L. W.↗

Preliminary results of mapping urban land cover with Seasat SAR imagery

The detectability of urban land cover types is explored using digitally processed Seasat SAR imagery of the Denver, Colorado area. Test sites within the metropolitan area were selected to include a cross section of Anderson, et. al. Level II land cover classes and cover types representative of the urban area growth stages. Using the Image 100 interactive processing system each test site was level sliced in an attempt to define specific reflectance boundaries for each cover type and to determine the spectral and spatial characteristics of homogeneous response regions. The rural-urban fringe boundary was readily definable, but a precise Level I and Level II land cover classification was not possible. High density housing could be separated from low density housing and from parks, but reflectance values were often look angle dependent. Confusion between some water and vegetation responses also posed problems.

Henderson, F. M.↗

Ignition dynamics of a laminar diffusion flame in the field of a vortex embedded in a shear flow

The role of streamwise-spanwise vorticity interactions that occur in turbulent shear flows on flame/vortex interactions is examined by means of asymptotic analysis and numerical simulation in the limit of small Mach number. An idealized model is employed to describe the interaction process. The model consists of a one-step, irreversible Arrhenius reaction between initially unmixed species occupying adjacent half-planes which are then allowed to mix and react in the presence of a streamwise vortex embedded in a shear flow. It is found that the interaction of the streamwise vortex with shear gives rise to small-scale velocity oscillations which increase in magnitude with shear strength. These oscillations give rise to regions of strong temperature gradients via viscous heating, which can lead to multiple ignition points and substantially decrease ignition times. The evolution in time of the temperature and mass-fraction fields is followed, and emphasis is placed on the ignition time and structure as a function of vortex and shear strength.

Macaraeg, Michele G.↗

Sensitivity of organized convective storms to model grid spacing in current and future climates

Mesoscale convective systems (MCSs) are complexes of thunderstorms that become organized and cover hundreds of kilometres over several hours. MCSs are prolific rain producers in the tropics and mid-latitudes and are the major cause of warm-season flooding. Traditionally, climate models have difficulties in simulating MCSs partly due to the misrepresentation of complex process interactions that operate across a large range of scales. Significant improvements in simulating MCSs have been found in kilometre-scale models that explicitly simulate deep convection. However, these models operate in the grey zone of turbulent motion and have known deficiencies in simulating small-scale processes (e.g. entrainment, vertical mass transport). Here, we perform mid-latitude idealized ensemble MCS simulations under current and future climate conditions in three atmospheric regimes: hydrostatic (12 km horizontal grid spacing; Δx), non-hydrostatic (Δx = 4, 2 and 1 km) and large eddy scale (Δx = 500 m and 250 m). Our results show a dramatic improvement in simulating MCS precipitation, movement, cold pools, and cloud properties when transitioning from 12 km to 4 km Δx. Decreasing Δx beyond 4 km results in modest improvements except for up- and downdraft sizes, average vertical mass fluxes, and cloud top height and temperature, which continue to change. Most important for climate modelling is that Δx = 4 km simulations reliably capture most MCS climate change signals compared to those of the Δx = 250 m runs. Significantly different climate change signals are found in Δx = 12 km runs that overestimate extreme precipitation changes by up to 100%.

54 ENVIRONMENTAL SCIENCES↗