Engineering topics
Chipman, Richard
Publications and source records attributed to Chipman, Richard.
Racoons ( Procyon Lotor ) Show Higher Trypanosoma Cruzi Detection Rates than Virginia Opossums ( Didelphis Virginiana ) in South Carolina, USA
Chagas disease, a significant public health concern in the Americas, is caused by a protozoan parasite, Trypanosoma cruzi. The life cycle of T. cruzi involves kissing bugs (Triatoma spp.) functioning as vectors and mammalian species serving as hosts. Raccoons (Procyon lotor) and opossums (Didelphis virginiana) have been identified as important reservoir species in the life cycle of T. cruzi, but prevalence in both species in the southeastern US is currently understudied. We quantified T. cruzi prevalence in these two key reservoir species across our study area in South Carolina, US, and identified factors that may influence parasite detection. We collected whole blood from 183 raccoons and 126 opossums and used PCR to detect the presence of T. cruzi. We then used generalized linear models with parasite detection status as a binary response variable and predictor variables of land cover, distance to water, sex, season, and species. Our analysis indicated that raccoons experienced significantly higher parasite detection rates than Virginia opossums, with T. cruzi prevalence found to be 26.5% (95% confidence interval [CI], 20.0–33.8) in raccoons and 10.5% (95% CI, 5.51–17.5) in opossums. Altogether, our results concur with previous studies, in that T. cruzi is established in reservoir host populations in natural areas of the southeastern US.
Impact of suntracking on Space Station controllability
The multibody dynamics of the Space Station is studied as affected by the suntracking motions of the photovotaic arrays. Dynamic responses are simulated for the Station being controlled by control moment gyros (CMGs). Controllability is shown to be a function of flight orientation, stage (inertial properties, CP-CG offset) and the suntracking dynamics. For certain combinations of these parameters, the aerodynamic, inertial disturbances and motor torques from alpha joint(s) arising from near-perfect suntracking are too large for the control moment gyro system to control. However, by imposing slight restrictions on the dynamics of the suntracking, CMGs are able to provide Station attitude stability with excellent pointing performance and an excellent microgravity environment.
Motion of a spacecraft with magnetic damper
Three methods of numerically simulating the motion of a spacecraft with a magnetic damper are compared. Simulations of motion of the initial assembly stage of Space Station Freedom show that results obtained with the first approach are in general agreement with those based on the second approach, while results from the third method are incorrect unless the spacecraft is nearly at rest in a local-vertical-local-horizontal reference frame. Simulations based on the second method proceed much more quickly than simulations based on the first. An integral of equations of motion governing the behavior of a spacecraft, and a sphere, which is part of the damper is presented. The integral can be used to test the results of numerical integrations performed in connection with the first and second approaches.
Adaptive control applied to Space Station attitude control system
This paper presents an adaptive control approach to enhance the performance of current attitude control system used by the Space Station Freedom. The proposed control law was developed based on the direct adaptive control or model reference adaptive control scheme. Performance comparisons, subject to inertia variation, of the adaptive controller and the fixed-gain linear quadratic regulator currently implemented for the Space Station are conducted. Both the fixed-gain and the adaptive gain controllers are able to maintain the Station stability for inertia variations of up to 35 percent. However, when a 50 percent inertia variation is applied to the Station, only the adaptive controller is able to maintain the Station attitude.
Mass property identification - A comparison study between extended Kalman filter and neuro-filter approaches
Two algorithms, extended Kalman filter and neuro-filter, are formulated to perform mass property identification for the Space Station Freedom. Control moment gyros that are part of the Station's basic momentum management system are chosen to provide input excitation in the form of applied torques. These torques together with the measured angular body rate responses are supplied to the filters. From these data, both algorithms are shown to accurately identify the station mass properties when excitation levels are high and balanced between axes. The neuro-filter, however, is shown to be more robust and to perform well even with weakly persistent, unbalanced signals contaminated with noise.