No description available.

Head injuries are very common in daily life and in war field. Head injuries are classified into open and closed. The mechanical mechanisms involved in closed head injuries are very different from those in open head injuries. Closed head injuries are more often re-ported with the use of protective device such as helmets. Helmets were found effective in reducing open head injuries, but less effective for closed head injuries. Finite element modeling is an effective and efficient tool for investigating head injuries. In this thesis, a two-dimensional finite element model was constructed based on a Mag-netic Resonance Image (MRI) scan data from a patient. MATLAB programming was used to extract the information from the MRI scan data. The finite element model was then used to investigate factors affecting closed head injuries. As a new contribution to closed head injury study, the fluid component in the human head, CSF, was studied by a group of comparative simulations. The other three factors, elasticity modulus of the cra-nium, contact area of impact, and impact duration were also investigated. Their effects on reducing the strain values in the brain were measured. Investigation results show that, increasing elasticity modulus of the cranium, contact area of impact and impact duration are very helpful to reduce the strain values in the brain. Helmet is helpful to protect people from closed head injuries because it can change all these three factors by using different shell stiffness and different padding material. The cerebrospinal fluid is effective in protecting the brain from impacts, as a fluid is able to reduce normal strains and filter nearly all shear strains transferred to the brain. It indicates that if a layer of fluid could be added as a layer in a protective helmet, the helmet would be more effective in protecting the brain. Conclusions obtained from the investigations are helpful for preventing closed head injuries and for improving design of protective devices such as helmets.

This study examined leaf area index (LAI) and relationships with corresponding tree growth, climate and soil characteristics across New Zealand forest plantations. The aim of this study was to determine if quick measures of projected leaf area across environmental gradients of New Zealand were an accurate indicator of site quality. Projected leaf areas of Pinus radiata D Don and Cupressus lusitanica Mills seedlings were measured using a Li-Cor LAI-2000 plant canopy analyser at 22 locations representing the soil and climatic diversity across New Zealand plantation forests. Seedlings planted at 40 000 stems per hectare were used to test treatment effects of fertiliser, site disturbance and species over a 4 year period. It was hypothesised that collected climate and soil information would explain differences in LAI development patterns across sites as the canopies approached site and seasonal maxima. Averaged across sites Cupressus lusitanica 7.28 (± 2.59 Std.) m2 m-2 had significantly (p = 0.0094) greater projected LAIs than Pinus radiata 6.47 (± 2.29) m2m-2. Maximum site LAI (LAImax) varied from 2.9 to 11.8 m2 m-2 for Pinus radiata and from 3.1 to 12.6 m2 m-2 for Cupressus lusitanica. LAImax of both species was significantly and positively correlated with vapour pressure deficit, soil carbon, nitrogen, phosphorous and CEC, but negatively with solar radiation, temperature and soil bulk density. A seasonal model of LAI across sites illustrated an 8.5% fluctuation in LAI of established canopies over the course of a year. Despite considerable variation in climate and soil characteristics across sites the combined effects of LAI at harvest and temperature were significantly correlated with site productivity (r2 = 0.84 and 0.76 for Pinus radiata and Cupressus lusitanica respectively). A national model of LAImax (r2 = 0.96) was proposed for Pinus radiata across climate and soil environments and the significance of LAImax as a component of site quality monitoring tools is discussed.

Head injuries are very common in daily life and in war field. Head injuries are classified into open and closed. The mechanical mechanisms involved in closed head injuries are very different from those in open head injuries. Closed head injuries are more often re-ported with the use of protective device such as helmets. Helmets were found effective in reducing open head injuries, but less effective for closed head injuries. Finite element modeling is an effective and efficient tool for investigating head injuries. In this thesis, a two-dimensional finite element model was constructed based on a Mag-netic Resonance Image (MRI) scan data from a patient. MATLAB programming was used to extract the information from the MRI scan data. The finite element model was then used to investigate factors affecting closed head injuries. As a new contribution to closed head injury study, the fluid component in the human head, CSF, was studied by a group of comparative simulations. The other three factors, elasticity modulus of the cra-nium, contact area of impact, and impact duration were also investigated. Their effects on reducing the strain values in the brain were measured. Investigation results show that, increasing elasticity modulus of the cranium, contact area of impact and impact duration are very helpful to reduce the strain values in the brain. Helmet is helpful to protect people from closed head injuries because it can change all these three factors by using different shell stiffness and different padding material. The cerebrospinal fluid is effective in protecting the brain from impacts, as a fluid is able to reduce normal strains and filter nearly all shear strains transferred to the brain. It indicates that if a layer of fluid could be added as a layer in a protective helmet, the helmet would be more effective in protecting the brain. Conclusions obtained from the investigations are helpful for preventing closed head injuries and for improving design of protective devices such as helmets.

No description available.

This thesis is concerned with subspace identification and its applications for controller performance assessment and process modeling from closed-loop data. A joint input-output closed-loop subspace identification method is developed which provides consistent estimation of the subspace matrices and the noise covariance matrix required for the LQG benchmark curve estimation. Subspace LQG benchmark is also used for performance assessment of the cascade supervisory-regulatory control systems. Three possible scenarios for LQG control design and performance improvement are discussed for this structure. A closed-loop subspace identification method is also provided for estimation of the subspace matrices necessary for performance assessment. A method of direct step model estimation from closed-loop data is provided using subspace identification. The variance calculation required for this purpose can be performed using the proposed method. The variances are used for weighted averaging on the estimated Markov parameters to attenuate the noise influence on the final step response estimation. / Process Control

Typescript. / Thesis (Ph. D.)--University of Hawaii at Manoa, 1986. / Bibliography: leaves 119-129. / Photocopy. / viii, 129 leaves, bound ill. 29 cm

Univ., Diss.--Strasbourg, 2003.

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves 275-283). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves 275-283). Also available on the Internet.