Fostering Strong Interactions Between Industry and Academia

This paper highlights a number of key issues in the development and execution of joint university-industry engineering projects. Government funding reductions have lead to decreased support of university research and economic forces have driven corporations to reduce or eliminate internal R&D centers. These are two driving factors behind the renewed ties between universities and industries. In developing a plan for a joint research project and when working together towards its solution, both sides need to be cognizant of their respective roles to ensure a successful partnership

Quality and inspection of machining operations: Review of condition monitoring and CMM inspection techniques 2000 to present

In order to consistently produce quality parts, many aspects of the manufacturing process must be carefully monitored, controlled, and measured. The methods and techniques by which to accomplish these tasks has been the focus of numerous studies in recent years. With the rapid advances in computing technology, the complexity and overhead that can be feasibly incorporated in any developed technique has dramatically improved. Thus, techniques that would have been impractical for implementation just a few years ago can now be realistically applied. This rapid growth has resulted in a wealth of new capabilities for improving part and process quality and reliability. In this paper, overviews of recent advances that apply to machining are presented. Moreover, due to the relative significance of two particular machining aspects, this review focuses specifically on research publications pertaining to using tool condition monitoring and coordinate measurement machines to improve the machining process. Tool condition has a direct effect on part quality and is discussed first. The application of tool condition monitoring as it applies to turning, drilling, milling, and grinding is presented. The subsequent section provides recommendations for future research opportunities. The ensuing section focuses on the use of coordinate measuring machines in conjunction with machining and is subdivided with respect to integration with machining tools, inspection planning and efficiency, advanced controller feedback, machine error compensation, and on-line tool calibration, in that specific order and concludes with recommendations regarding where future needs remain

Development of an advanced Compton camera with gaseous TPC and scintillator

A prototype of the MeV gamma-ray imaging camera based on the full reconstruction of the Compton process has been developed. This camera consists of a micro-TPC that is a gaseous Time Projection Chamber (TPC) and scintillation cameras. With the information of the recoil electrons and the scattered gamma-rays, this camera detects the energy and incident direction of each incident gamma-ray. We developed a prototype of the MeV gamma-ray camera with a micro-TPC and a NaI(Tl) scintillator, and succeeded in reconstructing the gamma-rays from 0.3 MeV to 1.3 MeV. Measured angular resolutions of ARM (Angular Resolution Measure) and SPD (Scatter Plane Deviation) for 356 keV gamma-rays were $18^\circ$ and $35^\circ$, respectively.Comment: 4 pages, 5 figures. Proceedings of the 6th International Workshop On Radiation Imaging Detector

Development of an XSPEC-Based Spectral Analysis System for the Coded-Aperture Hard X-ray Balloon Payload EXITE2

We present the spectral analysis system for the second-generation Energetic X-ray Imaging Telescope Experiment (EXITE2) balloon payload. EXITE2 is an imaging hard X-ray telescope using a coded-aperture mask and a NaI/CsI phoswich detector operating in the energy range 20--600 keV. The instrument was flown on a high-altitude scientific balloon from Ft. Sumner, NM on 1997 May 7-8. We describe the details of the EXITE2 spectral analysis system, with emphasis on those aspects peculiar to coded-aperture instruments. In particular, we have made our analysis compatible with the standard X-ray spectral fitting package XSPEC by generating a response matrix in the appropriate format including all the effects of a coded-aperture system. The use of XSPEC, which may be a first for coded-aperture data, permits great flexibility in the fitting of spectral models. The additional effects of our phoswich system, or any other detector-specific considerations, may be easily included as well. We test our spectral analysis using observations of the Crab Nebula, and find that the EXITE2 Crab spectrum is consistent with those recorded by previous instruments operating in this energy range.Comment: 17 pages LaTeX, 6 figures, accepted to Astroparticle Physic

Inspection strategy for LIGA microstructures using a programmable optical microscope.

The LIGA process has the ability to fabricate very precise, high aspect ratio mesoscale structures with microscale features [l]. The process consists of multiple steps before a final part is produced. Materials native to the LIGA process include metals and photoresists. These structures are routinely measured for quality control and process improvement. However, metrology of LIGA structures is challenging because of their high aspect ratio and edge topography. For the scale of LIGA structures, a programmable optical microscope is well suited for lateral (XU) critical dimension measurements. Using grayscale gradient image processing with sub-pixel interpolation, edges are detected and measurements are performed. As with any measurement, understanding measurement uncertainty is necessary so that appropriate conclusions are drawn from the data. Therefore, the abilities of the inspection tool and the obstacles presented by the structures under inspection should be well understood so that precision may be quantified. This report presents an inspection method for LIGA microstructures including a comprehensive assessment of the uncertainty for each inspection scenario

Tracking and imaging gamma ray experiment (TIGRE) for 1 to 100 MEV gamma ray astronomy

A large international collaboration from the high energy astrophysics community has proposed the Tracking and Imaging Gamma Ray Experiment (TIGRE) for future space observations. TIGRE will image and perform energy spectroscopy measurements on celestial sources of gamma rays in the energy range from 1 to 100 MeV. This has been a difficult energy range experimentally for gamma ray astronomy but is vital for the future considering the recent exciting measurements below 1 and above 100 MeV. TIGRE is both a double scatter Compton and gamma ray pair telescope with direct imaging of individual gamma ray events. Multi‐layers of Si strip detectors are used as Compton and pair converters CsI(Tl) scintillation detectors are used as a position sensitive calorimeter. Alternatively, thick GE strip detectors may be used for the calorimeter. The Si detectors are able to track electrons and positrons through successive Si layers and measure their directions and energy losses. Compton and pair events are completely reconstructed allowing each event to be imaged on the sky. TIGRE will provide an order‐of‐magnitude improvement in discrete source sensitivity in the 1 to 100 MeV energy range and determine spectra with excellent energy and excellent angular resolutions. It’s wide field‐of‐view of π sr permits observations of the entire sky for extended periods of time over the life of the mission

Advection-Dominated Accretion and the Spectral States of Black Hole X-Ray Binaries: Application to Nova Muscae 1991

We present a self-consistent model of accretion flows which unifies four distinct spectral states observed in black hole X-ray binaries: quiescent, low, intermediate and high states. In the quiescent, low and intermediate states, the flow consists of an inner hot advection-dominated part extending from the black hole horizon to a transition radius and an outer thin disk. In the high state the thin disk is present at all radii. The model is essentially parameter-free and treats consistently the dynamics of the accretion flow, the thermal balance of the ions and electrons, and the radiation processes in the accreting gas. With increasing mass accretion rate, the model goes through a sequence of stages for which the computed spectra resemble very well observations of the four spectral states; in particular, the low-to-high state transition observed in black hole binaries is naturally explained as resulting from a decrease in the transition radius. We also make a tentative proposal for the very high state, but this aspect of the model is less secure. We test the model against observations of the soft X-ray transient Nova Muscae during its 1991 outburst. The model reproduces the observed lightcurves and spectra surprisingly well, and makes a number of predictions which can be tested with future observations.Comment: 68 pages, LaTeX, includes 1 table (forgotten in the previous version) and 14 figures; submitted to The Astrophysical Journa

An Analysis and Improvement of the Predictive Control Integrating Component

integrator wind-up and, therefore, it is recommended that separate weighting be used with a modified integrating component predictive controller. The separate weighting also improves the designers intuition with respect to tuning the controller, significantly reducing the time required to generate desired closed loop responses. References Clarke, D. W., and Mohtadi, C, 1987, "Properties of Generalized Predictive Control," World Congress IFAC, Munich. Cutler, C. R., and Ramaker, B. L., 1979, "Dynamic Matrix Control-A Computer Control Algorithm," A.I.Ch.E., 86th National Meeting, Apr. Kurfess, T. R., Whitney, D. E., and Brown, M. L., 1988, "Verification of a Dynamic Grinding Model," ASME JOURNAL OF DYNAMIC SYSTEMS, MEAS-UREMENT, AND CONTROL, Dec., Vol. 110, Kurfess, T. R., 1989 "Predictive Control of a Robotic Weld Bead Grinding System," Ph.D. thesis, MIT Department of Mechanical Engineering. Kurfess, T. R., and Whitney, D. E., 1989, "Predictive Control of a Robotic Grinding System," Proceedings of the NMTBA Eastern Manufacturing Technology Conference, Hartford, CT, Oct. Kurfess, T. R., Whitney, D. E., 1989, "An Analysis and Improvement of the Predictive Control Integrating Component," ASME JOURNAL OF DYNAMIC SYS-TEMS, MEASUREMENT, AND CONTROL, submitted Dec. Kwakernaak, H., and Sivan, R., 1972 Introduction The usefulness of observers for real-time state estimation of linear dynamic systems based on measured system outputs is well known. Procedures for designing observers Another approach to robust state estimation has centered upon the fact that the estimated state is often used for feedback control. Hence, the criterion for observer design in these cases is to reduce the effect of modeling errors on the controlled system response. The work of The current work on robust state estimation using observers is motivated by the need to estimate pressure and temperature fields in thermoplastic injection molding processes, based on a few measurement locations in the mold cavity. Robustness of the estimate to errors in the process model is essential for this application given the complexity of the process. The initial use of the estimated pressure and temperature fields is for more effective process monitoring rather than for feedback control. The robustness of the state estimates obtained using observers, in the presence of system modeling error, is examined in this paper following the procedure of Determination of State Estimation Error Bound • Consider the linear time-invariant system described by x{t)=Ax(t) + Bu(t) y(t)=Cx(t) (1) subject to the initial condition x(0) = x 0 where A, B, and C are (nxn), (nxp), and (mxn) matrices, respectively, and x(t), u{t), and y(t) are («xl), (pxl) and (m x 1) vectors, respectively. A full order observer is designed Copyright © 1993 by ASME based on this model to estimate the state x(t). The observer is described by x(t) =AJt(t) +B c u(t)+L(y(t) -y(t)) y(t)=Cx(t) (2) subject to the initial condition Note that modeling errors are permitted only in the A and B matrices and not in the C matrix. Let the estimation error be defined by Manipulation of subject to the initial condition e(0) = x(0)-x(0) = e 0 (5) The eigenvalues of the augmented system described by (1) and (4) are those of A and F c . We assume that the input u{f) is bounded in magnitude and that all the eigenvalues of A have negative real parts, thus ensuring that the estimation error is bounded if all the eigenvalues of F c also have negative real parts. The solution of where M being the modal matrix corresponding to F c and A a diagonal matrix with the eigenvalues of F c as the diagonal elements. Extension of the results obtained here to the case of repeated eigenvalues is relatively straightforward. Taking norms of both sides of Eq. (6), we get C[ being the real part of the observer pole farthest to the right in the complex plane, assumed to be negative here. Id represents the Euclidean norm of any (n x 1) vector v and IIP! represents the spectral norm of any (n x ri) matrix P above. Also, k(M) is the condition number of the (n x ri) matrix M and is equal to IIMII. HAT 1 ! Note that the expression within curly brackets on the right hand side of Eq. (7) depends on the observer eigenvalues and not on the eigenvectors associates with these eigenvalues. The dependence of the state estimation error bound on these eigenvectors is solely via the condition number k(M) of the modal matrix corresponding to F c . Therefore, for competing observer designs with the same eigenvalues, the only difference is in the modal matrix M. The other terms within the curly brackets would be identical for such competing designs. Equation The result obtained here that the eigenvectors corresponding to the observer eigenvalues be chosen to be as nearly mutually orthogonal as possible to reduce the norm of the state estimation error seems to be a natural extension of a result obtained by The suggested observer design guideline does not address the issue of observer eigenvalue selection despite the fact that eigenvalue selection affects the estimation error. Thus, selection of observer eigenvalues without reference to consequences for estimation error may well lead to more robust observer designs being overlooked. Futhermore, Eq. (7) provides only a bound on the estimation error norm. Therefore, it is possible that even if two observer designs differ only in their eigenvector selections, the actual state estimation error norm may in some cases be lower for the design which yields a higher value of k(M) and hence of the error bound. This is less likely to occur, however, if the difference in the values of k(M) for the competing designs is large. Finally, the results obtained here are valid only for cases where the C matrix is known exactly. The procedure for eigenvector selection and observer gain computation follows that of D'Azzo and Houpis (1988). Since the eigenvectors and reciprocal eigenvectors of a matrix are known to be mutually orthogonal, the procedure begins with selection of the reciprocal eigenvectors of F c to be as nearly orthogonal as possible and normalized to have Euclidean norms of unity. S(\ i ) = (A c T -\ i IC T ) for the n specified eigenvalues of F c . At this point in the observer design, the available freedom in eigenvector assignment is used to obtain as nearly mutually orthogonal a set of reciprocal eigenvectors as is possible. The observer gain matrix is then given by Example of Observer Design Consider one dimensional heat conduction in a bar insulated at both ends, governed by the equation where c is the thermal diffusivity of the bar and u(r, t) is the temperature at the location r and time t. It is assumed here that two temperature sensors are located on the bar, one at each end. Using the two measurements provided by the sensors, we need to estimate the temperature distribution in the bar. It is also assumed that the initial temperature distribution in the bar may be unknown. A third order lumped parameter approximation of the distributed parameter system is developed using the modal expansion method. This lumped parameter model is described in a normalized form by The elements of x are the normalized weighting factors on the responses of the corresponding modes, c' is a normalized version of c. It is assumed that the actual value of c' is 0.11, while for observer design, a value of 0.09 is assumed, indicating about 18 percent error. The elements of the C matrix depend only on the boundary conditions and the form of the partial differential Eq. and yields a condition number of the modal matrix of F c , after equilibration, of 3.43. In design 2, the reciprocal eigenvectors are chosen to get a poorer condition number of the modal matrix of F c , equal to 31.44. The observer gain matrix for this design is given by It should be noted here, as an indication of the restricted nature of the results of There is no guarantee, however, that the norm of the state estimation error will always be lower if the observer is designed as indicated here. In fact, if the initial state estimation error vector is dominated by one component, or if the errors in some of the parameters of the A and B matrices are dominant over the others, the relationship between the state estimation error norms may not be the same as the relationship between the error bounds indicated by Eq. Conclusions In this paper, we have derived an expression for an upper bound on the norm of the estimation error for an observer, in the presence of errors in the system A and B matrices and in the estimated initial conditions. It is shown that, in designing observers for multi-output systems using eigenstructure assignment, if the eigenvectors of the F c matrix are chosen to be as nearly mutually orthogonal as possible, a smaller bound on the state estimation error is obtained and thus may lead to more accurate state estimation. This is demonstrated by means of an example. The approach presented seems most appropriate in the absence of any a priori information on the initial state or the nature of the modeling errors. References Introduction This paper is concerned with the problem of identifying the input-output relationship of an unknown nonlinear dynamical system. Classical adaptive control of deterministic linear systems whose state variables are not all observed makes use of the separation principle (Narendra and Annaswamy, 1989) which says, in effect, that the problems of constructing an observer and parameter estimator can be considered separately. When the system is not observable it is not possible to construct an observer to recover the full state. Furthermore, when the system is nonlinear the separation principle no longer applies, and hence conventional adaptive identification and control techniques offer little hope of effective control of partially observed nonlinear systems. In this paper we show that these difficulties can be avoided by using neural networks instead. Neural networks are already successfully applied in control theory and system identification. In a recent paper, Narandra and Parthasarathy (1990) formalized a unified approach to solving nonlinear identification and control problems using multilayered neural networks. Chen (1990) applied multilayer neural network to nonlinear self-tuning tracking problems. Chu et al. (1990) implemented a Hopfield network on identifying time-varying linear systems. Various learning architectures for training neural net controller are outlined in Psaltis et al. (1988) and some interesting applications of neural networks in adaptive control can be found in Goldenthal an

An Intense Gamma-Ray Flare of PKS1622-297

We report the observation by the Compton Gamma Ray Observatory of a spectacular flare of radio source PKS 1622-297. A peak flux of 17E-6 cm^-2 s^-1 (E > 100 MeV) was observed. The corresponding isotropic luminosity is 2.9E49 erg/s. We find that PKS 1622-297 exhibits gamma-ray intra-day variability. A flux increase by a factor of at least 3.6 was observed to occur in less than 7.1 hours (with 99% confidence). Assuming an exponential rise, the corresponding doubling time is less than 3.8 hours. A significant flux decrease by a factor of ~2 in 9.7 hours was also observed. Without beaming, the rapid flux change and large isotropic luminosity are inconsistent with the Elliot-Shapiro condition (assuming that gas accretion is the immediate source of power for the gamma-rays). This inconsistency suggests that the gamma-ray emission is beamed. A minimum Doppler factor of 8.1 is implied by the observed lack of pair-production opacity (assuming x-rays are emitted co-spatially with the gamma-rays). Simultaneous observation by EGRET and OSSE finds a spectrum adequately fit by a power law with photon index of -1.9. Although the significance is not sufficient to establish this beyond doubt, the high-energy gamma-ray spectrum appears to evolve from hard to soft as a flare progresses.Comment: 14 pages, 4 figures, 1 tabl

The Concordance Cosmic Star Formation Rate: Implications from and for the Supernova Neutrino and Gamma Ray Backgrounds

We constrain the Cosmic Star Formation Rate (CSFR) by requiring that massive stars produce the observed UV, optical, and IR light while at the same time not overproduce the Diffuse Supernova Neutrino Background as bounded by Super-Kamiokande. With the massive star component so constrained we then show that a reasonable choice of stellar Initial Mass Function and other parameters results in SNIa rates and iron yields in good agreement with data. In this way we define a `concordance' CSFR that predicts the optical SNII rate and the SNIa contribution to the MeV Cosmic Gamma-Ray Background. The CSFR constrained to reproduce these and other proxies of intermediate and massive star formation is more clearly delineated than if it were measured by any one technique and has the following testable consequences: (1) SNIa contribute only a small fraction of the MeV Cosmic Gamma-Ray Background, (2) massive star core-collapse is nearly always accompanied by a successful optical SNII, and (3) the Diffuse Supernova Neutrino Background is tantalizingly close to detectability.Comment: Improved discussion. Version accepted for publication in JCA