Radionuclide imaging correlatives of heart rate impairment during maximal exercise testing

A lower than normal heart rate response to maximal dynamic exercise, known as chronotropic incompetence or heart rate impairment, has been demonstrated to have a poor prognosis. In order to better describe patients with this finding, 156 men with coronary heart disease were evaluated. All patients were studied with maximal exercise testing, including measurements of oxygen consumption, exercise electrocardiograms, thallium scintigraphy and radionuclide ventriculography. Chronotropic incompetence was defined as a maximal heart rate 1 standard error of the estimate below the regression line of age versus maximal heart rate on two separate exercise tests. In patients so defined, mean maximal oxygen consumption was significantly lowered and angina was the major reason for stopping exercise on the treadmill. Patients with chronotropic incompetence not limited by angina had more evidence of myocardial scar and dysfunction and had a greater prevalence of three vessel coronary disease than did patients with a normal heart rate response. Radionuclide testing results suggest that among patients with chronotropic incompetence, those with angina have a better prognosis than those who do not have angina but who may have myocardial dysfunction

Optimal Power Management Strategy for Energy Storage with Stochastic Loads

In this paper, a power management strategy (PMS) has been developed for the control of energy storage in a system subjected to loads of random duration. The PMS minimises the costs associated with the energy consumption of specific systems powered by a primary energy source and equipped with energy storage, under the assumption that the statistical distribution of load durations is known. By including the variability of the load in the cost function, it was possible to define the optimality criteria for the power flow of the storage. Numerical calculations have been performed obtaining the control strategies associated with the global minimum in energy costs, for a wide range of initial conditions of the system. The results of the calculations have been tested on a MATLAB/Simulink model of a rubber tyre gantry (RTG) crane equipped with a flywheel energy storage system (FESS) and subjected to a test cycle, which corresponds to the real operation of a crane in the Port of Felixstowe. The results of the model show increased energy savings and reduced peak power demand with respect to existing control strategies, indicating considerable potential savings for port operators in terms of energy and maintenance costs

A Hierarchical Model Predictive Control Approach For Battery Systems

Applications in energy systems often require to simultaneously miti- gate long-term peak and short-term electricity costs. The long-term peak electricity demand cost, known as demand charge, constitutes an important component of the electricity bills for large consumption units like building campuses or manufacturing plants. This poses a challenging multiscale planning problem that should make decisions at fine timescales while mitigating long-term costs. We present a hierarchical model predictive control (MPC) approach to tackle this problem in the context of stationary battery systems. The goal is to determine the optimal charge-discharge policy for the battery to minimize the monthly demand charge. We also perform comparative studies of the proposed hierarchical MPC scheme and standard MPC schemes that use ad-hoc approaches to handle the multiple timescales. In the proposed hierarchical MPC approach, we assume that the state of charge (SOC) policy is periodic, which allows us to cast the long-term planning problem as a tractable stochastic programming problem. Here, very period (e.g., a day or week) represents an operational scenario and we seek to determine targets for the periodic SOC levels and the peak cost. The long-term planner MPC communicates the periodic SOC targets and peak cost to a short-term MPC controller. The short-term MPC determines the intra-period charge/discharge policies (at high resolution) while meeting the targets of the long-term planning. We use a case study for a university campus to demonstrate that the hierarchical MPC scheme yields optimal demand charge and charge-discharge policy under nominal (perfect forecast) conditions. Under imperfect forecasts, we show that the hierarchical MPC scheme results in significant improvements in demand charge reduction over a standard MPC scheme that uses a discounting factor to capture long-term effects

The Impact of Enhanced and Non-Enhanced Biochars on the Catabolism of 14C-Phenanthrene in Soil

Biochar is a by-product from the pyrolysis of biomass and has a great potential in soil amendment due to its carbon and nutrient-rich properties. The aim of this study was to investigate the impact of increasing amounts (0, 0.01, 0.1, 0.2, 0.5 and 1.0%) of two types of biochar (so-called enhanced and non-enhanced) to soil on the biodegradation of 14C-phenanthrene. Enhanced biochar contains inoculants which are designed to potentially stimulate microbial activity and promote biological function in soil. After 100 d of incubation, the addition of 0.5% and 1% enhanced (EbioC) and non-enhanced biochars (NEbioC) led to longer lag phases, reduced rates and extents of 14C-phenanthrene in amended soil. However, in soils amended with 0.01%, 0.1% and 0.2% amendments, extents of mineralisation of 14C-phenanthrene increased and were found to be higher in the EBioC- as compared to the NEbioC-amended soils. Increasing soil-phenanthrene contact time also increased 14C-phenanthrene mineralisation in soil which had received smaller amounts of EBioC. Application of both EbioC and NEbioC also enriched the soil microbial populations during the incubation. However, it was found that phenanthrene-degrading microbial populations declined as soil contact time increased; this was particularly true for soils receiving larger amounts of due to reduction in the mobile/bioaccessible fraction of the phenanthrene in soil. The findings revealed the importance of the type and amount of biochar that may be added to soil to stimulate or enhance organic contaminant biodegradation

Active sensors for health monitoring of aging aerospace structures

A project to develop non-intrusive active sensors that can be applied on existing aging aerospace structures for monitoring the onset and progress of structural damage (fatigue cracks and corrosion) is presented. The state of the art in active sensors structural health monitoring and damage detection is reviewed. Methods based on (a) elastic wave propagation and (b) electro-mechanical (NM) impedance technique are sighted and briefly discussed. The instrumentation of these specimens with piezoelectric active sensors is illustrated. The main detection strategies (E/M impedance for local area detection and wave propagation for wide area interrogation) are discussed. The signal processing and damage interpretation algorithms are tuned to the specific structural interrogation method used. In the high-frequency EIM impedance approach, pattern recognition methods are used to compare impedance signatures taken at various time intervals and to identify damage presence and progression from the change in these signatures. In the wave propagation approach, the acoustic-ultrasonic methods identifying additional reflection generated from the damage site and changes in transmission velocity and phase are used. Both approaches benefit from the use of artificial intelligence neural networks algorithms that can extract damage features based on a learning process. Design and fabrication of a set of structural specimens representative of aging aerospace structures is presented. Three built-up specimens, (pristine, with cracks, and with corrosion damage) are used. The specimen instrumentation with active sensors fabricated at the University of South Carolina is illustrated. Preliminary results obtained with the E/M impedance method on pristine and cracked specimens are presented