On the use of autonomous unmanned vehicles in response to hazardous atmospheric release incidents

Recent events have induced a surge of interest in the methods of response to releases of hazardous materials or gases into the atmosphere. In the last decade there has been particular interest in mapping and quantifying emissions for regulatory purposes, emergency response, and environmental monitoring. Examples include: responding to events such as gas leaks, nuclear accidents or chemical, biological or radiological (CBR) accidents or attacks, and even exploring sources of methane emissions on the planet Mars. This thesis presents a review of the potential responses to hazardous releases, which includes source localisation, boundary tracking, mapping and source term estimation. [Continues.]</div

Adaptive Sampling for Learning Gaussian Processes Using Mobile Sensor Networks

This paper presents a novel class of self-organizing sensing agents that adaptively learn an anisotropic, spatio-temporal Gaussian process using noisy measurements and move in order to improve the quality of the estimated covariance function. This approach is based on a class of anisotropic covariance functions of Gaussian processes introduced to model a broad range of spatio-temporal physical phenomena. The covariance function is assumed to be unknown a priori. Hence, it is estimated by the maximum a posteriori probability (MAP) estimator. The prediction of the field of interest is then obtained based on the MAP estimate of the covariance function. An optimal sampling strategy is proposed to minimize the information-theoretic cost function of the Fisher Information Matrix. Simulation results demonstrate the effectiveness and the adaptability of the proposed scheme

Plume Source Localization and Boundary Prediction

Plume location and prediction using mobile sensors is the main contribution of this thesis. Plume concentration values measured by chemical sensors at different locations are used to estimate the source of the plume. This is achieved by employing a stochastic approximation technique to localize the source and compare its performance to the nonlinear least squares method. The source location is then used as the initial estimate for the boundary tracking problem. Sensor measurements are used to estimate the parameters and the states of the state space model of the dynamics of the plume boundary. The predicted locations are the reference inputs for the LQR controller. Measurements at the new locations (after the correction of the prediction error) are added to the set of data to refine the next prediction process. Simulations are performed to demonstrate the viability of the methods developed. Finally, interpolation using the sensors locations is used to approximate the boundary shape

A survey on gas leakage source detection and boundary tracking with wireless sensor networks

Gas leakage source detection and boundary tracking of continuous objects have received a significant research attention in the academic as well as the industries due to the loss and damage caused by toxic gas leakage in large-scale petrochemical plants. With the advance and rapid adoption of wireless sensor networks (WSNs) in the last decades, source localization and boundary estimation have became the priority of research works. In addition, an accurate boundary estimation is a critical issue due to the fast movement, changing shape, and invisibility of the gas leakage compared with the other single object detections. We present various gas diffusion models used in the literature that offer the effective computational approaches to measure the gas concentrations in the large area. In this paper, we compare the continuous object localization and boundary detection schemes with respect to complexity, energy consumption, and estimation accuracy. Moreover, this paper presents the research directions for existing and future gas leakage source localization and boundary estimation schemes with WSNs

Review of sensing methodologies for estimation of combustion metrics

For reduction of engine-out emissions and improvement of fuel economy, closed-loop control of the combustion process has been explored and documented by many researchers. In the closed-loop control, the engine control parameters are optimized according to the estimated instantaneous combustion metrics provided by the combustion sensing process. Combustion sensing process is primarily composed of two aspects: combustion response signal acquisition and response signal processing. As a number of different signals have been employed as the response signal and the signal processing techniques can be different, this paper did a review work concerning the two aspects: combustion response signals and signal processing techniques. In-cylinder pressure signal was not investigated as one of the response signals in this paper since it has been studied and documented in many publications and also due to its high cost and inconvenience in the application

In-cylinder pressure resonance analysis for trapped mass estimation in automotive engines

This thesis presents a new application for in-cylinder pressure sensors in internal combustion engines. The new method takes profit of the high-frequency content of the in-cylinder pressure signal to determine the speed of sound evolution during the expansion stroke and combines this estimation with the low-frequency content of the pressure signal and a volume estimation to obtain a measurement of the trapped mass. The new method is based on the studies of the resonance phenomenon in pent-roof combustion chambers and proposes three calibration procedures to determine the resonant frequency evolution when bowl-in-piston geometries are considered. The Fourier transform has been modified in order to include harmonics with frequency variations, which allows a rapid identification of the resonant modes with no need of time-frequency analysis, e.g. STFT or WD. The main limitation of the method resides in the resonance excitation, which may be insufficient in low-load conditions, such as idle. An observer is presented to overcome that problem. The observer takes into account the dynamics of the sensors, the dynamics at the intake manifold, and combines current flow sensors with intermittent measurements, such as the trapped mass obtained by the resonance method, to provide the system with accurate and robust measurements of the trapped mass, the EGR, and the composition at the exhaust. The trapped mass obtained by the resonance method has been compared with auxiliary methods in various experimental facilities: in a SI engine, where no EGR exist, the differences founded were below 1%, in a conventional CI light-duty engine the average of the differences over 808 operating conditions accounted for a 2.64 %, in a research heavy-duty RCCI engine, with EGR, port fuel gasoline, and direct diesel injections, the average difference was 2.17 %, and in a research two-strokes single cylinder engine, where significant short-circuit and residual gases exist, the differences founded were 4.36 %. In all the studied cases the differences founded with the reference estimation can be attributed to the auxiliary method employed and its expected error. In order to demonstrate the potential of the resonance method four applications for control and diagnosis of internal combustion engines have been proposed: the estimation of residuals in engines with NVO, the prediction of knock in SI engines, the estimation of the exhaust gases temperature, and a NOx model for CI engines. In the four applications the method was compared with current methodologies and with additional sensors, demonstrating the improvement in accuracy and a cycle-to-cycle resolution.Esta tesis presenta una nueva aplicación para los sensores de presión en cámara. El nuevo método utiliza el contenido de alta frecuencia de la señal de presión en cámara para estimar la evolución de la velocidad del sonido durante la expansión de los gases de escape y combina esta estimación con el contenido de baja frecuencia de la presión en cámara y el volumen instantáneo de la cámara para obtener una medida de la masa atrapada. El nuevo método está basado en los estudios de la resonancia en cámaras de combustión cilíndricas y propone tres procedimientos de calibración para estimar la evolución de la frecuencia de resonancia en cámaras de combustión con bowl. La transformada de Fourier ha sido modificada para considerar harmónicos con frecuencias que varían en el tiempo, lo que permite una rápida identificación de los modos de resonancia sin necesidad de utilizar un análisis en tiempo frecuencia, como por ejemplo STFT o WD. La principal limitación del método es la necesidad de excitación suficiente de la resonancia, que puede impedir su uso en condiciones de baja carga como el ralentí. Para solventar este problema se ha diseñado un observador. El observador incluye las dinámicas de los sensores, las dinámicas del colector de admisión, y combina los sensores actuales de flujo con medidas intermitentes (como la medida ofrecida por el nuevo método de la resonancia) para obtener medidas de la masa atrapada, del EGR y de la composición en el escape precisas y robustas. La medida de la masa atrapada obtenida por el método de la resonancia ha sido comparado con métodos auxiliares en diferentes instalaciones experimentales: en un motor SI, sin EGR, las diferencias con los sensores eran menores del 1%, en un motor convencional CI la media de las diferencias sobre 808 puntos de operación distintos ha sido de 2.64 %, en un motor de investigación con EGR, con inyección gasolina en el colector e inyección directa de diesel, las diferencias fueron de 2.17 %, y en un motor de investigación de dos tiempos, donde existían grandes cantidades de corto-circuito y gases residuales, las diferencias fueron de 4.36 %. En todos los casos estudiados las diferencias encontradas pueden ser atribuidas a los errores que caracterizan los métodos auxiliares utilizados para obtener la medida de referencia. Finalmente, para demostrar el potencial del método se han desarrollado cuatro aplicaciones para control y diagnóstico de motores de combustión interna alternativos: la estimación de gases residuales en motores con NVO, la predicción de knock en motores SI, la estimación de la temperatura de los gases de escape, y un modelo de NOx para motores CI. En las cuatro aplicaciones el método ha sido comparado con los sistemas de medidas actuales y con sensores adicionales, demostrando mejoras importantes en la precisión de la medida y una resolución de un solo ciclo.Aquesta tesi presenta una nova aplicació per als sensors de pressió en cambra. El nou mètode utilitza el contingut d'alta freqüència del senyal de pressió en cambra per estimar l'evolució de la velocitat del so durant l'expansió dels gasos d'eixida i combina aquesta estimació amb el contingut de baixa freqüència de la pressió en cambra i el volum instantani de la cambra per obtenir una mesura de la massa atrapada. El nou mètode està desenvolupat dels estudis de la ressonància en cambres de combustió cilíndriques i proposa tres procediments de calibratge per estimar l'evolució de la freqüència de ressonància en cambres de combustió amb bowl. La transformada de Fourier ha sigut modificada per considerar harmònics amb freqüències que varien en el temps, el que permet una ràpida identificació dels modes de ressonància sense necessitat d'utilitzar una anàlisi en temps-freqüència, com per exemple la STFT o la WD. La principal limitació del mètode és la necessitat d'excitació suficient de la ressonància, que pot impedir el seu ús en condicions de baixa càrrega, com al ralentí. Per solucionar aquest problema s'ha desenvolupat un observador. L'observador inclou les dinàmiques dels sensors, les dinàmiques del col·lector d'admissió, i combina els sensors actuals de flux amb mesures intermitents (com l'obtinguda pel nou mètode de la ressonància) per obtenir mesures de la massa atrapada, del EGR i de la composició d'eixida precises i robustes. La mesura de la massa atrapada obtinguda pel mètode de la ressonància ha sigut comparada en mètodes auxiliars en diferents instal·lacions experimentals: a un motor SI, sense EGR, les diferencies amb els sensors estaven per davall de l'1 %, a un motor convencional CI la mitja de les diferències sobre 808 punts d'operació diferents ha sigut de 2.64 %, a un motor d'investigació, en EGR, en injecció gasolina en el col·lector i injecció directa de dièsel, les diferències van ser de 2.17 %, i a un motor d'investigació de dos temps, on existien grans quantitats de curtcircuit i residuals, les diferencies foren de 4.36 %. En tots els casos estudiats les diferències trobades poden ser atribuïdes als errors que caracteritzen els mètodes auxiliars utilitzats per obtenir la mesura de referència. Finalment, per demostrar el potencial del mètode s'han desenvolupat quatre aplicacions per al control i diagnòstic de motors de combustió interna alternatius: l'estimació de gasos residuals en motors amb NVO, la predicció de knock en motors SI, l'estimació de la temperatura dels gasos d'eixida, i un model de NOx per a motors CI. En les quatre aplicacions el mètode ha sigut comparat amb els sistemes de mesures actuals i amb sensors addicionals, demostrant millores importants en la precisió de la mesura i una resolució de solament un cicle.Bares Moreno, P. (2017). In-cylinder pressure resonance analysis for trapped mass estimation in automotive engines [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/9042

Integration of intermittent measurement from in-cylinder pressure resonance in a multi-sensor mass flow estimator

[EN] A novel technique of trapped mass determination, based on the in-cylinder pressure resonance, has been recently published by the authors. However, the method only works when sufficient resonance intensity exists and the current formulation might preclude its implementation in real-time due to excessive computational burden. The present paper proposes an iterative algorithm for reducing the number of operations, an adaptive filter to identify faulty measurements and a Kalman filter that combines several sensors and models, currently used in commercial light-duty engines, to ensure a continous estimation of trapped mass, air mass, and exhaust gas recirculation (EGR). The filter is implemented using experimental data of a EURO 6 light-duty engine in a world harmonize light-duty test cycle (WLTC), showing the potential of being implemented in real driving conditions with robustness and harnessing a new measurement to improve the accuracy and response of current estimations.Guardiola, C.; Pla Moreno, B.; Bares-Moreno, P.; Peyton Jones, J. (2019). Integration of intermittent measurement from in-cylinder pressure resonance in a multi-sensor mass flow estimator. Mechanical Systems and Signal Processing. 131:152-165. https://doi.org/10.1016/j.ymssp.2019.05.052S15216513

Airborne chemical sensing with mobile robots

Airborne chemical sensing with mobile robots has been an active research areasince the beginning of the 1990s. This article presents a review of research work in this field,including gas distribution mapping, trail guidance, and the different subtasks of gas sourcelocalisation. Due to the difficulty of modelling gas distribution in a real world environmentwith currently available simulation techniques, we focus largely on experimental work and donot consider publications that are purely based on simulations

Estimation of the Concentration from a Moving Gaseous Source in the Atmosphere Using a Guided Sensing Aerial Vehicle

The estimation of the gas concentration (process-state) associated with a stationary or moving source using a sensing aerial vehicle (SAV) is considered. The dispersion from such a gaseous source into the ambient atmosphere is representative of an accidental or deliberate release of chemicals, or a release of gases from biological systems. Estimation of the concentration field provides a superior ability for source localization, assessment of possible adverse impacts, and eventual containment. The abstract and finite-dimensional approximation framework presented couples theoretical estimation and control with computational fluid dynamics methods. The gas dispersion (process) model is based on the advection-diffusion equation with variable eddy diffusivities and ambient winds. Cases are considered for a 2D and 3D domain. The state estimator is a modified Luenberger observer with a €�collocated€� filter gain that is parameterized by the position of the SAV. The process-state (concentration) estimator is based on a 2D and 3D adaptive, multigrid, multi-step finite-volume method. The grid is adapted with local refinement and coarsening during the process-state estimation in order to improve accuracy and efficiency. The motion dynamics of the SAV are incorporated into the spatial process and the SAV€™s guidance is directly linked to the performance of the state estimator. The computational model and the state estimator are coupled in the sense that grid-refinement is affected by the SAV repositioning, and the guidance laws of the SAV are affected by grid-refinement. Extensive numerical experiments serve to demonstrate the effectiveness of the coupled approach