Combustion Phasing Modeling for Control of Spark-Assisted Compression Ignition Engines

Substantial fuel economy improvements for light-duty automotive engines demand novel combustion strategies. Low temperature combustion (LTC) demonstrates potential for significant fuel efficiency improvement; however, control complexity is an impediment for real-world transient operation. Spark-assisted compression ignition (SACI) is an LTC strategy that applies a deflagration flame to generate sufficient energy to trigger autoignition in the remaining charge. For other LTC strategies, control of autoignition timing is difficult as there is no direct actuator for combustion phasing. SACI addresses this challenge by using a spark plug to initiate a flame that then triggers autoignition in a significant portion of the charge. The flame propagation phase limits the rate of cylinder pressure increase, while autoignition rapidly completes combustion. High dilution is generally required to maintain production-feasible reaction rates. This high dilution, however, increases the likelihood of flame quench, and therefore potential misfires. Mitigating these competing constraints requires careful mixture preparation strategies for SACI to be feasible in production. Operating a practical engine within this restrictive regime is a key modeling and control challenge. Current models are not sufficient for control-oriented work such as calibration optimization, transient control strategy development, and real-time control. To resolve the modeling challenge, a fast-running cylinder model is developed and presented in this work. It comprises of five bulk gas states and a fuel stratification model comprising of ten equal-mass zones within the cylinder. The zones are quasi-dimensional, and their state varies with crank angle to capture the effect of fuel spray and mixing. For each zone, combustion submodels predict flame propagation burn duration, autoignition phasing, and the concentration of oxides of nitrogen. During the development of the combustion submodels, both physics-based and data-driven techniques are considered. However, the best balance between accuracy and computational expense leads to the nearly exclusive selection of data-driven techniques. The data-driven models are artificial neural networks (ANNs), trained to an experimentally-validated one-dimensional (1D) engine reference model. The simplified model matches the reference 1D engine model with an R2 value of 70‒96% for key combustion parameters. The model requires 0.8 seconds to perform a single case, a 99.6% reduction from the reference 1D engine model. The reduced model simulation time enables rapid exploration of the control space. Over 250,000 cases are evaluated across the entire range of actuator positions. From these results, a transient-capable calibration is formulated. To evaluate the strength of the steady-state calibration, it is operated over a tip-in and tip-out. The response to the transients required little adjustment, suggesting the steady-state calibration is robust. The model also demonstrates the capability to adapt in-cylinder state and spark timing to offset combustion phasing disturbances. This positive performance suggests the candidate model developed in this work retains sufficient accuracy to be beneficial for control-oriented objectives. There are four contributions of this research: 1) a demonstration of the impact of combustion fundamentals on SACI combustion, 2) an identification of suitable techniques for data-driven modeling, 3) a quasi-dimensional fuel stratification model for radially-stratified engines, and 4) a comprehensive cylinder model that maintains high accuracy despite substantially reduced computational expense

Protocol for the effective feedback to improve primary care prescribing safety (EFIPPS) study : a cluster randomised controlled trial using ePrescribing data

High-risk prescribing in primary care is common and causes considerable harm. Feedback interventions to improve care are attractive because they are relatively cheap to widely implement. There is good evidence that feedback has small to moderate effects, but the most recent Cochrane review called for more high-quality, large trials that explicitly test different forms of feedback. The study is a three-arm cluster-randomised trial with general practices being randomised and outcomes measured at patient level. 262 practices in three Scottish Health Board areas have been randomised (94% of all possible practices). The two active arms receive different forms of prescribing safety data feedback, with rates of high-risk prescribing compared with a ‘usual care’ arm. Sample size estimation used baseline data from participating practices. With 85 practices randomised to each arm, then there is 93% power to detect a 25% difference in the percentage of high-risk prescribing (from 6.1% to 4.5%) between the usual care arm and each intervention arm. The primary outcome is a composite of six high-risk prescribing measures (antipsychotic prescribing to people aged ≥75 years; non-steroidal anti-inflammatory drug (NSAID) prescribing to people aged ≥75 without gastroprotection; NSAID prescribing to people prescribed aspirin/clopidogrel without gastroprotection; NSAID prescribing to people prescribed an ACE inhibitor/angiotensin receptor blocker and a diuretic; NSAID prescription to people prescribed an oral anticoagulant without gastroprotection; aspirin/clopidogrel prescription to people prescribed an oral anticoagulant without gastroprotection). The primary analysis will use multilevel modelling to account for repeated measurement of outcomes in patients clustered within practices. The study was reviewed and approved by the NHS Tayside Committee on Medical Research Ethics B (11/ES/0001). The study will be disseminated via a final report to the funder with a publicly available research summary, and peer reviewed publications

Phytophthora root and stem rot of soybean

Phytophthora sojae is a soil borne pathogen that in the past has caused very large economic losses. During the late 1970s, 300,000 soybean acres (approximately 10% of total soybean production in Ohio) were lost due to P. sojae. This disease has since been effectively managed predominately through the incorporation of single-gene mediated resistance but quantitative or partial resistance has been used as well. In fact, today, we can repeat 100% loss by planting soybean cultivars that were popular during earlier epidemics. Without high levels of resistance to this pathogen, many soybean acres would be lost each year to this disease. Phytophthora doesn’t forget and it doesn’t go away

Nickel-catalysed allylboration of aldehydes

A nickel catalyst for the allylboration of aldehydes is reported, facilitating the preparation of homoallylic alcohols in high diastereoselectivity. The observed diastereoselectivities and NMR experiments suggest that allylation occurs through a well-defined six-membered transition state, with nickel acting as a Lewis acid

Sub-system mechanical design for an eLISA optical bench

We present the design and development status of the opto-mechanical sub-systems that will be used in an experimental demonstration of imaging systems for eLISA. An optical bench test bed design incorporates a Zerodur® baseplate with lenses, photodetectors, and other opto-mechanics that must be both adjustable - with an accuracy of a few micrometers - and stable over a 0 to 40°C temperature range. The alignment of a multi-lens imaging system and the characterisation of the system in multiple degrees of freedom is particularly challenging. We describe the mechanical design of the precision mechanisms, including thermally stable flexure-based optical mounts and complex multi-lens, multi-axis adjuster mechanisms, and update on the integration of the mechanisms on the optical bench

Lay support for pregnant women with social risk: a randomised controlled trial

We sought evidence of effectiveness of lay support to improve maternal and child outcomes in disadvantaged families. Antenatal attendances were high in the standard care control and did not increase further with addition of the POW intervention (10.1 vs 10.1 (mean difference; MD) −0.00, 95% CI (95% CI −0.37 to 0.37)). In the powered subgroup of women with 2 or more social risk factors, mean EPDS (MD −0.79 (95% CI −1.56 to −0.02) was significantly better, although for all women recruited, no significant differences were seen (MD −0.59 (95% CI −1.24 to 0.06). Mother-to-infant bonding was significantly better in the intervention group for all women (MD −0.30 (95% CI −0.61 to −0.00) p=0.05), and there were no differences in other secondary outcomes. This trial demonstrates differences in depressive symptomatology with addition of the POW service in the powered subgroup of women with 2 or more social risk factors. Addition to existing evidence indicates benefit from lay interventions in preventing postnatal depression. This finding is important for women and their families given the known effect of maternal depression on longer term childhood outcomes

Data feedback and behavioural change intervention to improve primary care prescribing safety (EFIPPS):multicentre, three arm, cluster randomised controlled trial

Objective: To evaluate the effectiveness of feedback on safety of prescribing compared with moderately enhanced usual care. Design: Three arm, highly pragmatic cluster randomised trial. Setting and participants: 262/278 (94%) primary care practices in three Scottish health boards. Interventions: Practices were randomised to: "usual care," consisting of emailed educational material with support for searching to identify patients (88 practices at baseline, 86 analysed); usual care plus feedback on practice's high risk prescribing sent quarterly on five occasions (87 practices, 86 analysed); or usual care plus the same feedback incorporating a behavioural change component (87 practices, 86 analysed). Main outcome measures: The primary outcome was a patient level composite of six prescribing measures relating to high risk use of antipsychotics, non-steroidal anti-inflammatories, and antiplatelets. Secondary outcomes were the six individual measures. The primary analysis compared high risk prescribing in the two feedback arms against usual care at 15 months. Secondary analyses examined immediate change and change in trend of high risk prescribing associated with implementation of the intervention within each arm. Results: In the primary analysis, high risk prescribing as measured by the primary outcome fell from 6.0% (3332/55 896) to 5.1% (2845/55 872) in the usual care arm, compared with 5.9% (3341/56 194) to 4.6% (2587/56 478) in the feedback only arm (odds ratio 0.88 (95% confidence interval 0.80 to 0.96) compared with usual care; P=0.007) and 6.2% (3634/58 569) to 4.6% (2686/58 582) in the feedback plus behavioural change component arm (0.86 (0.78 to 0.95); P=0.002). In the pre-specified secondary analysis of change in trend within each arm, the usual care educational intervention had no effect on the existing declining trend in high risk prescribing. Both types of feedback were associated with significantly more rapid decline in high risk prescribing after the intervention compared with before. Conclusions: Feedback of prescribing safety data was effective at reducing high risk prescribing. The intervention would be feasible to implement at scale in contexts where electronic health records are in general use