PREDICTING THE STRENGTH OF WOOD-JOIST FLOORS.
Abstract : This study was intended to explore the relationships between strengths at first rupture predicted by linear and nonlinear models for wood-joist floors of a given configuration but having various combinations of joist material properties. The study produced two ways of altering linear models to account for the nonlinear behavior of nails in floors loaded to failure. The strength at first joist failure of 72 floors was analyzed using linear and nonlinear finite-element models and statistical comparisons. The results of the study are presented in two forms. The first is recommended factors by which the predicted failure loads from the linear analysis can be scaled to give failure loads consistent with the nonlinear analysis. The second is recommended substitute nail stiffness which can be used in a linear analysis to predict floor responses with near-equivalent accuracy as provided by a nonlinear analysis. The results presented are specific to the floor design used in this study, but similar techniques could be used to derive equivalent information for other floor designs.
FEAFLO: A program for the analysis of layered wood systems
Abstract A finite element method for the analysis of planar layered wood systems is described. The method includes the effects of slip between layers due to fastener deformations, orthotropic material properties and gaps in layers. The method was used in developing program FEAFLO (Finite Element Analysis of FLOors). Data computed at each node include the deflection, rotations, fastener forces and for each layer the axial displacements, axial forces, moments, shears and extreme fiber stresses. The method was verified by comparing measured and predicted behavior for T-beams and wood joist floors. A listing of program FEAFLO, written in ANSI FORTRAN IV, is given. The input and output data for an example floor are also given.
Fully Integrated Bidirectional CMOS-MEMS Flow Sensor With Low Power Pulse Operation
Leveraging More-than-Moore technology, we demonstrate an integrated CMOS MEMS flow sensor via a very compact system on chip (SoC) that can sense the bidirectional N2 gas flow. Our SoC features a very low-noise instrumentation amplifier that is implemented on a CMOS wafer and serves as a readout integrated circuit for a thermoresistive micro-calorimetric flow sensor which is fabricated on a MEMS wafer. A compact heterogeneous integration is achieved by combining the two wafers via the proprietary InvenSense AlN process. The measured sensitivity of our CMOS MEMS flow sensor is 98 mV/sccm which is three times better than the state-of-the-art counterpart. The flow range measured by our SoC is from −26 to 26 m/s (from −50 to 50 sccm). Moreover, the pulsed heater operation makes this proposed SoC flow sensor a very low power (<9 mW) and, thus, a promising candidate for the Internet-of-Things applications in smart home/green buildings.