Analysis of cost and performance of physical security systems can be a complex, multi-dimensional problem. There are a number of point tools that address various aspects of cost and performance analysis. Increased interest in cost tradeoffs of physical security alternatives has motivated development of an architecture called Cost and Performance Analysis (CPA), which takes a top-down approach to aligning cost and performance metrics. CPA incorporates results generated by existing physical security system performance analysis tools, and utilizes an existing cost analysis tool. The objective of this architecture is to offer comprehensive visualization of complex data to security analysts and decision-makers.
In most probabilistic risk assessments, there is a set of accident scenarios that involves the physical responses of a system to environmental challenges. Examples include the effects of earthquakes and fires on the operability of a nuclear reactor safety system, the effects of fires and impacts on the safety integrity of a nuclear weapon, and the effects of human intrusions on the transport of radionuclides from an underground waste facility. The physical responses of the system to these challenges can be quite complex, and their evaluation may require the use of detailed computer codes that are very time consuming to execute. Yet, to perform meaningful probabilistic analyses, it is necessary to evaluate the responses for a large number of variations in the input parameters that describe the initial state of the system, the environments to which it is exposed, and the effects of human interaction. Because the uncertainties of the system response may be very large, it may also be necessary to perform these evaluations for various values of modeling parameters that have high uncertainties, such as material stiffnesses, surface emissivities, and ground permeabilities. The authors have been exploring the use of artificial neural networks (ANNs) as a means for estimating the physical responses of complex systems to phenomenological events such as those cited above. These networks are designed as mathematical constructs with adjustable parameters that can be trained so that the results obtained from the networks will simulate the results obtained from the detailed computer codes. The intent is for the networks to provide an adequate simulation of the detailed codes over a significant range of variables while requiring only a small fraction of the computer processing time required by the detailed codes. This enables the authors to integrate the physical response analyses into the probabilistic models in order to estimate the probabilities of various responses.
GaN etching can be affected by a wide variety of parameters including plasma chemistry and plasma density. Chlorine-based plasmas have been the most widely used plasma chemistries to etch GaN due to the high volatility of the GaCl{sub 3} and NCl etch products. The source of Cl and the addition of secondary gases can dramatically influence the etch characteristics primarily due to their effect on the concentration of reactive Cl generated in the plasma. In addition, high-density plasma etch systems have yielded high quality etching of GaN due to plasma densities which are 2 to 4 orders of magnitude higher than reactive ion etch (RIE) plasma systems. The high plasma densities enhance the bond breaking efficiency of the GaN, the formation of volatile etch products, and the sputter desorption of the etch products from the surface. In this study, the authors report GaN etch results for a high-density inductively coupled plasma (ICP) as a function of BCl{sub 3}:Cl{sub 2} flow ratio, dc-bias, chamber-pressure, and ICP source power. GaN etch rates ranging from {approximately}100 {angstrom}/min to > 8,000 {angstrom}/min were obtained with smooth etch morphology and anisotropic profiles.
Enhanced tribological properties have been observed after treatment with pulsed high power ion beams, which results in rapid melting and resolidification of the surface. The authors have treated and tested 440C martensitic stainless steel (Fe-17 Cr-1 C). Ti and Al samples were sputter coated and ion beam treated to produce surface alloying. The samples were treated at the RHEPP-I facility at Sandia National Laboratories (0.5 MV, 0.5--1 {micro}s at sample location, <10 J/cm{sup 2}, 1--5 {micro}m ion range). They have observed a reduction in size of second phase particles and other microstructural changes in 440C steel. The hardness of treated 440C increases with ion beam fluence and a maximum hardness increase of a factor of 5 is obtained. Low wear rates are observed in wear tested of treated 440C steel. Surface alloyed Ti-Pt layers show improvements in hardness up to a factor of 3 over untreated Ti, and surface alloys of Al-Si result in a hardness increase of a factor of two over untreated Al. Both surface alloys show increased durability in wear testing. Rutherford Backscattering (RBS) measurements show overlayer mixing to the depth of the melted layer. X-ray Diffraction (XRD) and TEM confirm the existence of metastable states within the treated layer. Treated layer depths have been measured from 1--10 {micro}m.
The mission of the national laboratories has changed from weapon design and production to stockpile maintenance. Design engineers are becoming few in number and years worth of experience is about to be lost. What will happen when new weapons are designed or retrofits need to be made? Who will know the lessons learned in the past? What process will be followed? When and what software codes should be used? Intelligent design is the answer to the questions posed above for weapon design; for any design. An interactive design development environment will allow the designers of the future access to the knowledge of yesterday, today and tomorrow. Design guides, rules of thumb, lessons learned, production capabilities, production data, process flow, and analysis codes will be included in intelligent design. An intelligent design environment is being developed as a heuristic, knowledge based system and as a diagnostic design tool. The system provides the framework for incorporating rules of thumb from experienced design engineers, available manufacturing processes, including the newest ones, and manufacturing databases, with current data, to help reduce design margins. The system also has the capability to access analysis and legacy codes appropriately. A modular framework allows for various portions to be added or deleted based on the application. This paper presents the driving forces for developing an intelligent design environment and an overview of the system. This overview will include the system architecture and how it relates to the capture and utilization of design and manufacturing knowledge. The paper concludes with a discussion of realized and expected benefits.
The detection and refocus of moving targets in SAR imagery is of interest in a number of applications. In this paper the authors address the problem of refocusing a blurred signature that has by some means been identified as a moving target. They assume that the target vehicle velocity is constant, i.e., the motion is in a straight line with constant speed. The refocus is accomplished by application of a two-dimensional phase function to the phase history data obtained via Fourier transformation of an image chip that contains the blurred moving target data. By considering separately the phase effects of the range and cross-range components of the target velocity vector, they show how the appropriate phase correction term can be derived as a two-parameter function. They then show a procedure for estimating the two parameters, so that the blurred signature can be automatically refocused. The algorithm utilizes optimization of an image domain contrast metric. They present results of refocusing moving targets in real SAR imagery by this method.
Sandia National Laboratories has conducted research in chemical sensing and analysis of explosives for many years. Recently, that experience has been directed towards detecting mines and unexploded ordnance (UXO) by sensing the low-level explosive signatures associated with these objects. The authors focus has been on the classification of UXO in shallow water and anti-personnel/anti tank mines on land. The objective of this work is to develop a field portable chemical sensing system which can be used to examine mine-like objects (MLO) to determine whether there are explosive molecules associated with the MLO. Two sampling subsystems have been designed, one for water collection and one for soil/vapor sampling. The water sampler utilizes a flow-through chemical adsorbent canister to extract and concentrate the explosive molecules. Explosive molecules are thermally desorbed from the concentrator and trapped in a focusing stage for rapid desorption into an ion-mobility spectrometer (IMS). The authors describe a prototype system which consists of a sampler, concentrator-focuser, and detector. The soil sampler employs a light-weight probe for extracting and concentrating explosive vapor from the soil in the vicinity of an MLO. The chemical sensing system is capable of sub-part-per-billion detection of TNT and related explosive munition compounds. They present the results of field and laboratory tests on buried landmines which demonstrate their ability to detect the explosive signatures associated with these objects.
The disposition of the large backlog of plutonium residues at the Rocky Flats Environmental Technology Site (Rocky Flats) will require interim storage and subsequent shipment to a waste repository. Current plans call for disposal at the Waste Isolation Pilot Plant (WIPP) and the transportation to WIPP in the TRUPACT-II. The transportation phase will require the residues to be packaged in a container that is more robust than a standard 55 gallon waste drum. Rocky Flats has designed the Pipe Overpack Container to meet this need. The potential for damage to this container during onsite storage in unhardened structures for several hypothetical accident scenarios has been addressed using finite element calculations. This report will describe the initial conditions and assumptions for these analyses and the predicted response of the container.
This paper describes a novel digital signal processing algorithm for adaptively detecting and identifying signals buried in noise. The algorithm continually computes and updates the long-term statistics and spectral characteristics of the background noise. Using this noise model, a set of adaptive thresholds and matched digital filters are implemented to enhance and detect signals that are buried in the noise. The algorithm furthermore automatically suppresses coherent noise sources and adapts to time-varying signal conditions. Signal detection is performed in both the time-domain and the frequency-domain, thereby permitting the detection of both broad-band transients and narrow-band signals. The detection algorithm also provides for the computation of important signal features such as amplitude, timing, and phase information. Signal identification is achieved through a combination of frequency-domain template matching and spectral peak picking. The algorithm described herein is well suited for real-time implementation on digital signal processing hardware. This paper presents the theory of the adaptive algorithm, provides an algorithmic block diagram, and demonstrate its implementation and performance with real-world data. The computational efficiency of the algorithm is demonstrated through benchmarks on specific DSP hardware. The applications for this algorithm, which range from vibration analysis to real-time image processing, are also discussed.
It has been recognized that nondestructive inspection (NDI) techniques and instruments that have proven themselves in the laboratory do not always perform as well under field conditions. In this paper the authors explore combinations of formal laboratory and field experimentation to characterize NDI processes as they may be implemented in field conditions. They also discuss appropriate modeling for probability of detection (POD) curves as applied to data gathered under field conditions. A case is made for expanding the more traditional two-parameter models to models using either three or four parameters. They use NDI data gathered from various airframe inspection programs to illustrate the points.
Si{sup +} implant activation efficiencies above 90%, even at doses of 5 {times} 10{sup 15} cm{sup {minus}2}, have been achieved in GaN by RTP at 1,400--1,500 C for 10 secs. The annealing system utilizes with MoSi{sub 2} heating elements capable of operation up to 1,900 C, producing high heating and cooling rates (up to 100 C{center_dot}s{sup {minus}1}). Unencapsulated GaN show severe surface pitting at 1,300 C, and complete loss of the film by evaporation at 1,400 C. Dissociation of nitrogen from the surface is found to occur with an approximate activation energy of 3.8 eV for GaN (compared to 4.4 eV for AlN and 3.4 eV for InN). Encapsulation with either rf-magnetron reactively sputtered or MOMBE-grown AlN thin films provide protection against GaN surface degradation up to 1,400 C, where peak electron concentrations of {approximately} 5 {times} 10{sup 20} cm{sup {minus}3} can be achieved in Si-implanted GaN. SIMS profiling showed little measurable redistribution of Si, suggesting D{sub Si} {le} 10{sup {minus}13} cm{sup 2}{center_dot}s{sup {minus}1} at 1,400 C . The implant activation efficiency decreases at higher temperatures, which may result from Si{sub Ga} to Si{sub N} site switching and resultant self-compensation.
In this paper the authors give a construction of wavelets which are (a) semi-orthogonal with respect to an arbitrary elliptic bilinear form a({center_dot},{center_dot}) on the Sobolev space H{sub 0}{sup 1}((0, L)) and (b) continuous and piecewise linear on an arbitrary partition of [0, L]. They illustrate this construction using a model problem. They also construct alpha-orthogonal Battle-Lemarie type wavelets which fully diagonalize the Galerkin discretized matrix for the model problem with domain IR. Finally they describe a hybrid basis consisting of a combination of elements from the semi-orthogonal wavelet basis and the hierarchical Schauder basis. Numerical experiments indicate that this basis leads to robust scalable Galerkin discretizations of the model problem which remain well-conditioned independent of {epsilon}, L, and the refinement level K.
Investment casting is an important method for fabricating a variety of high quality components in mechanical systems. Cast components, unfortunately, have a large design and gate/runner build time associated with their fabrication. In addition, casting engineers often require many years of actual experience in order to consistently pour high quality castings. Since 1989, Sandia National Laboratories has been investigating casting technology and software that will reduce the time overhead involved in producing quality casts. Several companies in the casting industry have teamed up with Sandia to form the FASTCAST Consortium. One result of this research and the formation of the FASTCAST consortium is the creation of the WinMod software, an expert casting advisor that supports the decision making process of the casting engineer through visualization and advice to help eliminate possible casting defects.
The effect of temperature on the reversible and irreversible capacities of disordered carbons derived from polymethacryonitrile (PMAN) and divinylbenzene (DVB) copolymers was studied in 1 M LiPF{sub 6}/ethylene carbonate (EC)-dimethyl carbonate (DMC) (1:1 v/v) solution by galvanostatic cycling. The kinetics of passive film formation were examined by complex-impedance spectroscopy. Temperatures of 5, 21, and 35 C were used in the study.
Electrical characteristics of hybrid power sources consisting of Li-ion cells and double layer capacitors were studied at 25 C and {minus}20 C. The cells were initially evaluated for pulse performance and then measured in hybrid modes of operation. Cells manufactured by Panasonic delivered pulses up to 3A and cells from A and T delivered 4A at 25 C before cell capacity dropped. Measured cell resistances were 0.15 ohms and 0.12 ohms, respectively. These measurements were repeated at {minus}20 C. Direct coupling of the cells and capacitors (dumb hybrid) extended the pulse limits to 5.6A using the Panasonic cells and 9A for the A and T cells. Operation in a smart hybrid mode using uncoupled cell/capacitor discharge allowed full cell capacity usage at 25 C and showed a factor of 5 improvement in delivered capacity at {minus}20 C.
The power requirements for an inverter application were specified to be 500 V at 360 A, or 180 kW per each of six 1-s pulses delivered over a period of 10 minutes. Conventional high-power sources (e.g., flywheels) could not meet these requirements and the use of a thermal battery was considered. The final design involved four, 125-cell, 50-kW modules connected in series. A module using the LiSi/CoS{sub 2} couple and all-Li (LiCI-LiBr-LiF minimum-melting) electrolyte was successfully developed and tested. A power level of over 40 kW was delivered during a 0.5-s pulse. This translates into a specific power level of over 9 kW/kg or 19.2 kW/L delivered from a module. The module was still able to deliver over 30 kW during a 1-s pulse after 10 minutes.
The ignition processes that take place during activation of a 16 cell, center hole fired thermal battery were examined by monitoring the voltage of each cell during activation. The average rise time of each cell to a voltage of 1.125 V was determined for the LiSi/LiCl-LiBr-LiF/FeS{sub 2} electrochemical system. The effects of heat pellet composition, center hole diameter, and the load on the activation parameters were examined for three different igniters. A large variability in individual cell performance was evident along with cell reversal, depending on the location of the cell in the stack. It was not possible to draw detailed statistical information of the relative ignition sequence due to the intrinsic large scatter in the data.
This paper reviews issues related to the use of aeroelastic tailoring as a cost-effective, passive means to shape the power curve and reduce loads. Wind turbine blades bend and twist during operation, effectively altering the angle of attack, which in turn affects loads and energy production. There are blades now in use that have significant aeroelastic couplings, either on purpose or because of flexible and light-weight designs. Since aeroelastic effects are almost unavoidable in flexible blade designs, it may be desirable to tailor these effects to the authors advantage. Efforts have been directed at adding flexible devices to a blade, or blade tip, to passively regulate power (or speed) in high winds. It is also possible to build a small amount of desirable twisting into the load response of a blade with proper asymmetric fiber lay up in the blade skin. (Such coupling is akin to distributed {delta}{sub 3} without mechanical hinges.) The tailored twisting can create an aeroelastic effect that has payoff in either better power production or in vibration alleviation, or both. Several research efforts have addressed different parts of this issue. Research and development in the use of aeroelastic tailoring on helicopter rotors is reviewed. Potential energy gains as a function of twist coupling are reviewed. The effects of such coupling on rotor stability have been studied and are presented here. The ability to design in twist coupling with either stretching or bending loads is examined also.
This report describes the numerical procedure used to implement the Green`s function method for solving the Poisson equation in two-dimensional (r,z) cylindrical coordinates. The procedure can determine the solution to a problem with any or all of the applied voltage boundary conditions, dielectric media, floating (insulated) conducting media, dielectric surface charging, and volumetric space charge. The numerical solution is reasonably fast, and the dimension of the linear problem to be solved is that of the number of elements needed to represent the surfaces, not the whole computational volume. The method of solution is useful in the simulation of plasma particle motion in the vicinity of complex surface structures as found in microelectronics plasma processing applications. This report is a stand-alone supplement to the previous Sandia Technical Report SAND98-0537 presenting the two-dimensional Cartesian Poisson solver.
The need for a reliable, fast, wireless telemetry system in the drilling industry is great but the technical challenge to develop such a system is huge. A downhole wireless telemetry system based on Surface Area Modulation (SAM) has been developed which involves the introduction of an electrically insulated gap near the bottom of an otherwise conductive drillstring. The electrical resistance of this gap can be modulated to alter the electrical characteristics of a circuit involving a surface power supply, the sections of the drillstring above and below the gap, the earth, and a nearby return electrode. These changes alter the current in the circuit, which can be monitored at the surface with an ammeter. Downhole data are encoded and transmitted to the surface as a pattern of current oscillations. In a field test, the SAM system successfully transmitted downhole information from depths of 1,400 ft below the fluid level to the surface at a rate of 110 baud. Electrical insulation on the outside of the simulated drillstring was required to achieve this level of performance. Electrically insulated tubing improved the data transmission rate at a given depth by more than an order of magnitude, and increased the maximum depth from which successful data telemetry could be achieved by more than a factor of two.
This study examines ergonomic stressors associated with front-end process tool maintenance, relates them to decreased machine utilization, and proposes solution strategies to reduce their negative impact on productivity. Member company ergonomists observed technicians performing field maintenance tasks on seven different bottleneck tools and recorded ergonomic stressors using SEMaCheck, a graphics-based, integrated checklist developed by Sandia National Laboratories. The top ten stressors were prioritized according to a cost formula that accounted for difficulty, time, and potential errors. Estimates of additional time on a task caused by ergonomic stressors demonstrated that machine utilization could be increased from 6% to 25%. Optimal solution strategies were formulated based on redesign budget, stressor cost, and estimates of solution costs and benefits
The concept of ``progressive Lattice Sampling`` as a basis for generating successive finite element response surfaces that are increasingly effective in matching actual response functions is investigated here. The goal is optimal response surface generation, which achieves an adequate representation of system behavior over the relevant parameter space of a problem with a minimum of computational and user effort. Such is important in global optimization and in estimation of system probabilistic response, which are both made much more viable by replacing large complex computer models of system behavior by fast running accurate approximations. This paper outlines the methodology for Finite Element/Lattice Sampling (FE/LS) response surface generation and examines the effectiveness of progressively refined FE/LS response surfaces in decoupled Monte Carlo analysis of several model problems. The proposed method is in all cases more efficient (generally orders of magnitude more efficient) than direct Monte Carlo evaluation, with no appreciable loss of accuracy. Thus, when arriving at probabilities or distributions by Monte Carlo, it appears to be more efficient to expend computer model function evaluations on building a FE/LS response surface than to expend them in direct Monte Carlo sampling. Furthermore, the marginal efficiency of the FE/LS decoupled Monte Carlo approach increases as the size of the computer model increases, which is a very favorable property.
This report represents the completion of a three-year Laboratory-Directed Research and Development (LDRD) program to investigate sub-wavelength surface relief structures fabricated by direct-write e-beam technology as unique and very high-efficiency optical elements. A semiconductor layer with sub-wavelength sized etched openings or features can be considered as a layer with an effective index of refraction determined by the fraction of the surface filled with semiconductor relative to the fraction filled with air or other material. Such as a layer can be used to implement planar gradient-index lenses on a surface. Additionally, the nanometer-scale surface structures have diffractive properties that allow the direct manipulation of polarization and altering of the reflective properties of surfaces. With this technology a single direct-write mask and etch can be used to integrate a wide variety of optical functions into a device surface with high efficiencies; allowing for example, direct integration of polarizing optics into the surface with high efficiencies; allowing for example, direct integration of polarizing optics into the surfaces of devices, forming anti-reflection surfaces or fabricating high-efficiency, high-numerical aperture lenses, including integration inside vertical semiconductor laser cavities.
This report summarizes work on the development of high-speed vertical cavity surface emitting lasers (VCSELs) for multi-gigabit per second optical data communications applications (LDRD case number 3506.010). The program resulted in VCSELs that operate with an electrical bandwidth of 20 GHz along with a simultaneous conversion efficiency (DC to light) of about 20%. To achieve the large electrical bandwidth, conventional VCSELs were appropriately modified to reduce electrical parasitics and adapted for microwave probing for high-speed operation.
Micromachining technologies, or Micro-Electro-Mechanical Systems (MEMS), enable the develop of low-cost devices capable of sensing motion in a reliable and accurate manner. Sandia has developed a MEMS fabrication process for integrating both the micromechanical structures and microelectronics circuitry of surface micromachined sensors, such as silicon accelerometers, on the same chip. Integration of the micromechanical sensor elements with microelectronics provides substantial performance and reliability advantages for MEMS accelerometers. A design team at Sandia was assembled to develop a micromachined silicon accelerometer capable of surviving and measuring very high accelerations (up to 50,000 times the acceleration due to gravity). The Sandia integrated surface micromachining process was selected for fabrication of the sensor due to the extreme measurement sensitivity potential associated with integrated microelectronics. Very fine measurement sensitivity was required due to the very small accelerometer proof mass (< 200 {times} 10{sup {minus}9} gram) obtainable with this surface micromachining process. The small proof mass corresponded to small sensor deflections which required very sensitive electronics to enable accurate acceleration measurement over a range of 1,000 to 50,000 times the acceleration due to gravity. Several prototype sensors, based on a suspended plate mass configuration, were developed and the details of the design, modeling, fabrication and validation of the device will be presented in this paper. The device was analyzed using both conventional lumped parameter modeling techniques and finite element analysis tools. The device was tested and performed well over its design range (the device was tested over a range of a few thousand G to 46,000 G, where 1 G equals the acceleration due to gravity).
