Abstract: A building security system of a building including one or more memory devices configured to store instructions causing one or more processors to receive door lock data collected from one or more sensors for one or more doors within the building indicating operation of the one or more doors, select a period for which the door lock data was collected, select a first door from the one or more doors of the building for which data is collected, and identify segments of the data indicating activity of the door. The instructions also apply a model to segments of the data indicating activity of the first door, compute a probability metric for each segment of the data, compute a combined probability score for the first door based on the computed probability metrics, and classify the first door as normally functioning or malfunctioning by comparing the combined probability score to a threshold.

Abstract: A method of enhancing a scan or design of an engineering component, including: obtaining a scan or a design of an engineering component and inputting the scan or design of the component into a computer, providing an input into the computer of at least one physical parameter relating to the design or the scan of the image, converting the input parameter into a histogram and/or a glyph that represents the value of the physical parameter, and embedding the histogram or glyph into the scan or design of the engineering component. A computer implemented method of designing a component uses a Conditional Generative Adversarial Network.

Abstract: A computer implemented method of assessing the suitability of a component, including: utilising a Conditional Generative Adversarial Network (cGAN), the cGAN network having an input, a generator and a discriminator; obtaining images or scans of manufactured components for both acceptable and non-acceptable components; training the discriminator of the cGAN with the images representing the acceptable and non-acceptable scans or images of a manufactured component; scanning or imaging a component to be assessed; and inputting the image or scan of a component to be assessed into the discriminator of the cGAN, wherein the output of the discriminator assesses if the scan or image is acceptable for use or not.

Abstract: A building security system of a building including one or more memory devices configured to store instructions causing one or more processors to receive door lock data collected from one or more sensors for one or more doors within the building indicating operation of the one or more doors, select a period for which the door lock data was collected, select a first door from the one or more doors of the building for which data is collected, and identify segments of the data indicating activity of the door. The instructions also apply a model to segments of the data indicating activity of the first door, compute a probability metric for each segment of the data, compute a combined probability score for the first door based on the computed probability metrics, and classify the first door as normally functioning or malfunctioning by comparing the combined probability score to a threshold.

Abstract: A method of designing a structure, such as an airfoil section. A first set of candidate designs is generated in a first optimisation process, each candidate design comprising a set of M design variables associated with an M-dimensional design space. A subset of the first set of candidate designs is selected. The selected subset of candidate designs is analysed by proper orthogonal decomposition or principal component analysis to generate an N-dimensional design space defined by N design variables, N being less than M. A second set of one or more candidate designs is then generated in a second optimisation process, each candidate design comprising a set of N design variables associated with the N-dimensional design space.

Abstract: A method of designing a structure, such as an airfoil section. A first set of candidate designs is generated in a first optimisation process, each candidate design comprising a set of M design variables associated with an M-dimensional design space. A subset of the first set of candidate designs is selected. The selected subset of candidate designs is analysed by proper orthogonal decomposition or principal component analysis to generate an N-dimensional design space defined by N design variables, N being less than M. A second set of one or more candidate designs is then generated in a second optimisation process, each candidate design comprising a set of N design variables associated with the N-dimensional design space.

Abstract: A method of identifying a configuration of an object, the method comprising the steps of: specifying a plurality of different object configurations; for each specified object configuration, using a first simulation procedure to simulate the specified conditions so as to generate data that can be used to evaluate the object configuration against the optimisation criterion; identifying a functional relationship between data generated for each specified object configuration; using the functional relationship and the optimisation criterion to select a data point, and identifying an object configuration corresponding thereto; and using a second simulation procedure, wherein the second simulation procedure comprises iteratively calculating values of variables characterising the object configuration until the values satisfy a convergence criterion, wherein for at least one of the specified object configurations, the first simulation procedure is completed before the values calculated therein satisfy the convergence

Abstract: A method of generating a multifidelity model of a system comprises the steps of obtaining training data from a high fidelity model of the system, providing a low fidelity model of the system, providing a kriging model to compensate for discrepancies between the high and low fidelity models, adjusting the kriging model to maximise the likelihood of the training data when the low fidelity model, compensated by the kriging model, is used to model the system, and generating a multifidelity model of the system based on the low fidelity model when compensated by the adjusted by the adjusted kriging model. The system may be a gas turbine or a part of a gas turbine for example a tail bearing housing.