The present research work has been carried out to develop a unified knowledge-based hybrid methodology combining regression-based, lumped parameter and finite element analyses that can be implemented in the initial phase of vehicle design resulting in a superior side crash performance. As a first step, a regression-based model (RBM) is developed between the injury parameter Thoracic Trauma Index (TTI) of the rear SID and characteristic side impact dynamic response variables such as rear door velocity (final) and intrusion supplementing an existing RBM for front TTI prediction. In order to derive the rear TTI RBM, existing public domain vehicle crash test data provided by NHTSA has been used. A computer-based tool with a Graphical User Interface (GUI) has been developed for obtaining possible solution sets of response variables satisfying the regression relations for both front and rear TTI. As a next step in the formulation of the present hybrid methodology for vehicle side impact safety design, a new Lumped Parameter Model (LPM) representing NHTSA side impact is developed. The LPM developed consists of body sub-systems like B-pillar, front door, rear door and rocker (i.e. sill) on the struck side of the vehicle, MDB, and “rest of the vehicle” as lumped masses along with representative nonlinear springs between them. It has been envisaged that for the initial conceptual design to progress, the targets of dynamic response variables obtained from RBM should yield a set of spring characteristics broadly defining the required vehicle side structure. However, this is an inverse problem of dynamics which would require an inordinate amount of time to be solved iteratively. Hence a knowledge-based approach is adopted here to link the two sets of variables i.e., the dynamic response parameters (such as average door and B-pillar velocities, door intrusion, etc.) and the stiffness and strength characteristics of the springs present in LPM. In effect, this mapping is accomplished with the help of an artificial neural network (ANN) algorithm (referred to as ANN_RBM_LPM in the current work). To generate the required knowledge database for ANN_RBM_LPM, one thousand cases of LPM chosen with the help of the Latin Hypercube technique are run with varying spring characteristics. The goal of finding the desired design solutions describing vehicle geometry in an efficient manner is accomplished with the help of a second ANN algorithm which links sets of dynamic spring characteristics with sets of sectional properties of doors, B-pillar and rocker (referred as ANN_LPM_FEM in the current work). The implementation of this approach requires creation of a knowledge database containing paired sets of spring characteristics and sectional details just mentioned. The effectiveness of the hybrid methodology comprising both ANN_RBM_LPM and ANN_LPM_FEM is finally illustrated by improving the side impact performance of a Honda Accord finite element model. Thus, the unique knowledge-based hybrid approach developed here can be deployed in real world vehicle safety design for both new and existing vehicles leading to enormous saving of time and costly design iterations.

This thesis work provides an insight into the design of Force-amplifying Compliant Mechanisms (FaCMs) that are integrated with micromachined resonant accelerometers to increase their sensitivity. An FaCM, by mechanically amplifying the inertial force, enhances the shift in the resonance frequency of the beams used for sensing the acceleration whose effect causes an axial force on the beams. An extensive study on different configurations of resonators namely, single beam resonator, single-ended tuning fork (SETF), and double-ended tuning fork (DETF), is carried out to gain insights about their resonant behavior. The influence of the boundary conditions on the sensor’s sensitivity emerged from the study. We found that not only the force-amplification factor but also the multi-axial stiffness of the FaCM and proof-mass influence the resonance frequency of the resonator as well as the bandwidth of the modified sensor for certain configurations but not all. Thus, four lumped parameters were identified to quantify the effectiveness of an FaCM. These parameters determine the boundary condition of the sensing beams and also the forces and the moment transmitted to them. Also presented in this work is a computationally efficient model, called the Lumped Parameter Model (LPM) for evaluation of the sensitivity. An analytical expression for the frequency-shift of the sensing resonator beams is obtained by considering the FaCM stiffness parameters as well as the lumped stiffness of the suspension of the inertial mass. Various FaCMs are evaluated and compared to understand how the four lumped parameters influence the sensor’s sensitivity. The FaCMs are synthesized using topology optimization to maximize the net amplification factor with the volume constraint. One of the FaCMs outperforms the lever by a factor of six. Microfabrication of resonant accelerometer coupled with FaCM and comb-drive actuator is carried out using a silicon-on-insulator process. Finally, the selection map technique, a compliant mechanism redesign methodology is used for enhancing the amplification of FaCMs. This technique provides scope for further design improvement in FaCMs for given sensor specifications.

Evaluation of the performance of a product and its components under impact loading is one of the key considerations in design. In order to assess resistance to damage or ability to absorb energy through plastic deformation of a structural component, impact testing is often carried out to obtain the 'Force - Displacement' response of the deformed component. In this context, it may be noted that load cells and accelerometers are commonly used as sensors for capturing impact responses. A drop-weight impact testing set-up consisting of a moving impactor head with a lightweight piezoresistive accelerometer and a strain gage based compression load cell mounted on it is used to carry out the impact tests. The basic objective of the present study is to assess the accuracy of responses recorded by the said transducers, when these are mounted on a moving impactor head. In the present work, a novel approach of theoretically evaluating the responses obtained from this drop-weight impact testing set-up for different axially loaded specimen has been executed with the formulation of an equivalent lumped parameter model (LPM) of the test set-up. For the most common configuration of a moving impactor head mounted load cell system in which dynamic load is transferred from the impactor head to the load cell, a quantitative assessment is made of the possible discrepancy that can result in load cell response. Initially, a 3-DOF (degrees-of-freedom) LPM is considered to represent a given impact testing set-up with the test specimen represented with a nonlinear spring. Both the load cell and the accelerometer are represented with linear springs, while the impacting unit comprising an impactor head (hammer) and a main body with the load cell in between are modelled as rigid masses. An experimentally obtained force-displacement response is assumed to be a nearly true behaviour of a specimen. By specifying an impact velocity to the rigid masses as an initial condition, numerical solution of the governing differential equations is obtained using Implicit (Newmark-beta) and Explicit (Central difference) time integration techniques. It can be seen that the model accurately reproduces the input load-displacement behaviour of the nonlinear spring corresponding to the tested component, ensuring the accuracy of these numerical methods. The nonlinear spring representing the test specimen is approximated in a piecewise linear manner and the solution strategy adopted and implemented in the form of a MATLAB script is shown to yield excellent reproduction of the assumed load-displacement behaviour of the test specimen. This prediction also establishes the accuracy of the numerical approach employed in solving the LPM system. However, the spring representing the load cell yields a response that qualitatively matches the assumed input load-displacement response of the test specimen with a lower magnitude of peak load. The accelerometer, it appears, may be capable of predicting more closely the load experienced by a specimen provided an appropriate mass of the impactor system i.e. impacting unit, is chosen as the multiplier for the acceleration response. Error between input and computed (simulated) responses is quantified in terms of root mean square error (RMSE). The present study additionally throws light on the dependence of time step of integration on numerical results. For obtaining consistent results, estimation of critical time step (increment) is crucial in conditionally stable central difference method. The effect of the parameters of the impact testing set-up on the accuracy of the predicted responses has been studied for different combinations of main impactor mass and load cell stiffness. It has been found that the load cell response is oscillatory in nature which points out to the need for suitable filtering for obtaining the necessary smooth variation of axial impact load with respect to time as well as deformation. Accelerometer response also shows undulations which can similarly be observed in the experimental results as well. An appropriate standard SAE-J211 filter which is a low-pass Butterworth filter has been used to remove oscillations from the computed responses. A load cell is quite capable of predicting the nature of transient response of an impacted specimen when it is part of the impacting unit, but it may substantially under-predict the magnitudes of peak loads. All the above mentioned analysis for a 3 DOF model have been performed for thin-walled tubular specimens made of mild steel (hat-section), an aluminium alloy (square cross-section) and a glass fibre-reinforced composite (circular cross-section), thus confirming the generality of the inferences drawn on the computed responses. Further, results obtained using explicit and implicit methodologies are compared for three specimens, to find the effect, if any, on numerical solution procedure on the conclusions drawn. The present study has been further used for investigating the effects of input parameters (i.e. stiffness and mass of the system components, and impact velocity) on the computed results of transducers. Such an investigation can be beneficial in designing an impact testing set-up as well as transducers for recording impact responses. Next, the previous 3 DOF model representing the impact testing set-up has been extended to a 5 DOF model to show that additional refinement of the original 3 DOF model does not substantially alter the inferences drawn based on it. In the end, oscillations observed in computed load cell responses are analysed by computing natural frequencies for the 3 DOF lumped parameter model. To conclude the present study, a 2 DOF LPM of the given impact testing set-up with no load cell has been investigated and the frequency of oscillations in the accelerometer response is seen to increase corresponding to the mounting resonance frequency of the accelerometer. In order to explore the merits of alternative impact testing set-ups, LPMs have been formulated to idealize test configurations in which the load cell is arranged to come into direct contact with the specimen under impact, although the accelerometer is still mounted on the moving impactor head. One such arrangement is to have the load cell mounted stationary on the base under the specimen and another is to mount the load cell on the moving impactor head such that the load cell directly impacts the specimen. It is once again observed that both these models accurately reproduce the input load-displacement behaviour of the nonlinear spring corresponding to the tested component confirming the validity of the model. In contrast to the previous set-up which included a moving load cell not coming into contact with the specimen, the spring representing the load cell in these present cases yields a response that more closely matches the assumed input load-displacement response of a test specimen suggesting that the load cell coming into direct contact with the specimen can result in a more reliable measurement of the actual dynamic response. However, in practice, direct contact of the load cell with the specimen under impact loading is likely to damage the transducer, and hence needs to be mounted on the moving head, resulting in a loss of accuracy, which can be theoretically estimated and corrected by the methodology investigated in this work.