Effective Stress Method for Piezocone Evaluation of S\u3csub\u3eu\u3c/sub\u3e

A simple piezocone model combines spherical cavity expansion theory and modified Cam Clay concepts to represent both the corrected cone tip resistance (qT) and penetration pore water pressure measured behind the tip (ubt). In closed form, the undrained shear strength (su) is shown to be a function of the effective friction angle (φ\u27), the plastic volumetric strain ratio (Λ), and the piezocone parameter (qT− ubt)· Parametric studies show that the model is relatively insensitive to variations in φ\u27 and Λ, thereby simplifying its form for practical use. The method is applied to results from laboratory calibration chamber tests on kaolinitic clay, as well as field data from eight intact clay sites reported in the literature. In addition to in-situ PCPT records, these clay deposits have known profiles of su evaluated from laboratory isotropically and anisotropically-consolidated undrained triaxial compression tests

Load tests on drilled shaft foundations in the Piedmont Province

Issued as Technical report, Project E-20-X1

Whither discrete time model predictive control?

This note proposes an efficient computational procedure for the continuous time, input constrained, infinite horizon, linear quadratic regulator problem (CLQR). To ensure satisfaction of the constraints, the input is approximated as a piecewise linear function on a finite time discretization. The solution of this approximate problem is a standard quadratic program. A novel lower bound on the infinite dimensional CLQR problem is developed, and the discretization is adaptively refined until a user supplied error tolerance on the CLQR cost is achieved. The offline storage of the required quadrature matrices at several levels of discretization tailors the method for online use as required in model predictive control (MPC). The performance of the proposed algorithm is then compared with the standard discrete time MPC algorithms. The proposed method is shown to be significantly more efficient than standard discrete time MPC that uses a sample time short enough to generate a cost close to the CLQR solution

Automating Vehicles by Deep Reinforcement Learning using Task Separation with Hill Climbing

Within the context of autonomous driving a model-based reinforcement learning algorithm is proposed for the design of neural network-parameterized controllers. Classical model-based control methods, which include sampling- and lattice-based algorithms and model predictive control, suffer from the trade-off between model complexity and computational burden required for the online solution of expensive optimization or search problems at every short sampling time. To circumvent this trade-off, a 2-step procedure is motivated: first learning of a controller during offline training based on an arbitrarily complicated mathematical system model, before online fast feedforward evaluation of the trained controller. The contribution of this paper is the proposition of a simple gradient-free and model-based algorithm for deep reinforcement learning using task separation with hill climbing (TSHC). In particular, (i) simultaneous training on separate deterministic tasks with the purpose of encoding many motion primitives in a neural network, and (ii) the employment of maximally sparse rewards in combination with virtual velocity constraints (VVCs) in setpoint proximity are advocated.Comment: 10 pages, 6 figures, 1 tabl

A comparison of GC-FID and PTR-MS toluene measurements in ambient air under conditions of enhanced monoterpene loading

Toluene was measured using both a gas chromatographic system (GC), with a flame ionization detector (FID), and a proton transfer reaction-mass spectrometer (PTR-MS) at the AIRMAP atmospheric monitoring station Thompson Farm (THF) in rural Durham, NH during the summer of 2004. Simultaneous measurements of monoterpenes, including alpha- and beta-pinene, camphene, Delta(3)-carene, and d-limonene, by GC-FID demonstrated large enhancements in monoterpene mixing ratios relative to toluene, with median and maximum enhancement ratios of similar to 2 and similar to 30, respectively. A detailed comparison between the GC-FID and PTR-MS toluene measurements was conducted to test the specificity of PTR-MS for atmospheric toluene measurements under conditions often dominated by biogenic emissions. We derived quantitative estimates of potential interferences in the PTR-MS toluene measurements related to sampling and analysis of monoterpenes, including fragmentation of the monoterpenes and some of their primary carbonyl oxidation products via reactions with H(3)O(+), O(2)(+) and NO(+) in the PTR-MS drift tube. The PTR-MS and GC-FID toluene measurements were in good quantitative agreement and the two systems tracked one another well from the instrumental limits of detection to maximum mixing ratios of similar to 0.5 ppbv. A correlation plot of the PTR-MS versus GC-FID toluene measurements was described by the least squares regression equation y=(1.13 +/- 0.02)x-(0.008 +/- 0.003) ppbv, suggesting a small similar to 13% positive bias in the PTR-MS measurements. The bias corresponded with a similar to 0.055 ppbv difference at the highest measured toluene level. The two systems agreed quantitatively within the combined 1 sigma measurement precisions for 60% of the measurements. Discrepancies in the measured mixing ratios were not well correlated with enhancements in the monoterpenes. Better quantitative agreement between the two systems was obtained by correcting the PTR-MS measurements for contributions from monoterpene fragmentation in the PTR-MS drift tube; however, the improvement was minor (\u3c10%). Interferences in the PTRMS measurements from fragmentation of the monoterpene oxidation products pinonaldehyde, caronaldehyde and alpha-pinene oxide were also likely negligible. A relatively large and variable toluene background in the PTR-MS instrument likely drove the measurement bias; however, the precise contribution was difficult to accurately quantify and thus was not corrected for in this analysis. The results from THF suggest that toluene can be reliably quantified by PTR-MS using our operating conditions (drift tube pressure, temperature and voltage of 2.0 mbar, 45 degrees C and 600V, respectively) under the ambient compositions probed. This work extends the range of field conditions under which PTR-MS validation studies have been conducted

Accelerated placental aging in early onset preeclampsia pregnancies identified by DNA methylation.

Aim: To determine whether dynamic DNA methylation changes in the human placenta can be used to predict gestational age. Materials & methods: Publicly available placental DNA methylation data from 12 studies, together with our own dataset, using Illumina Infinium Human Methylation BeadChip arrays. Results & conclusion: We developed an accurate tool for predicting gestational age of placentas using 62 CpG sites. There was a higher predicted gestational age for placentas from early onset preeclampsia cases, but not term preeclampsia, compared with their chronological age. Therefore, early onset preeclampsia is associated with placental aging. Gestational age acceleration prediction from DNA methylation array data may provide insight into the molecular mechanisms of pregnancy disorders.Benjamin T Mayne, Shalem Y Leemaqz, Alicia K Smith, James Breen, Claire T Roberts, Tina Bianco-Miott

Evaluating geoparameters of Maine sensitive clay by CPTU

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