The separation of hydrogen and carbon monoxide using polymer membranes

This work studies the development of polymer membranes for the separation of hydrogen and carbon monoxide from a syngas produced by the partial oxidation of natural gas. The CO product is then used for the large scale manufacture of acetic acid by reaction with methanol. A method of economic evaluation has been developed for the process as a whole and a comparison is made between separation of the H2/CO mixture by a membrane system and the conventional method of cryogenic distillation. Costs are based on bids obtained from suppliers for several different specifications for the purity of the CO fed to the acetic acid reactor. When the purity of the CO is set at that obtained by cryogenic distillation it is shown that the membrane separator offers only a marginal cost advantage. Cost parameters for the membrane separation systems have been defined in terms of effective selectivity and cost permeability. These new parameters, obtained from an analysis of the bids, are then used in a procedure which defines the optimum degree of separation and recovery of carbon monoxide for a minimum cost of manufacture of acetic acid. It is shown that a significant cost reduction is achieved with a membrane separator at the optimum process conditions. A method of "targeting" the properties of new membranes has been developed. This involves defining the properties for new (hypothetical -yet to be developed) membranes such that their use for the hydrogen/carbon monoxide separation will produce a reduced cost of acetic acid manufacture. The use of the targeting method is illustrated in the development of new membranes for the separation of hydrogen and carbon monoxide. The selection of polymeric materials for new membranes is based on molecular design methods which predict the polymer properties from the molecular groups making up the polymer molecule. Two approaches have been used. One method develops the analogy between gas solubility in liquids and that in polymers. The UNIFAC group contribution method is then used to predict gas solubility in liquids. In the second method the polymer Permachor number, developed by Salame, has been correlated with hydrogen and carbon monoxide permeabilities. These correlations are used to predict the permeabilities of gases through polymers. Materials have been tested for hydrogen and carbon monoxide permeabilities and improvements in expected economic performance have been achieved.

Simulating the value of collaboration in multi-actor conservation planning

The loss of habitat and biodiversity worldwide has led to considerable resources being spent for conservation purposes on actions such as the acquisition and management of land, the rehabilitation of degraded habitats, and the purchase of easements from private landowners. Prioritising these actions is challenging due to the complexity of the problem and because there can be multiple actors undertaking conservation actions, often with divergent or partially overlapping objectives. We use a modelling framework to explore this issue with a study involving two agents sequentially purchasing land for conservation. We apply our model to simulated data using distributions taken from real data to simulate the cost of patches and the rarity and co-occurence of species. In our model each agent attempted to implement a conservation network that met its target for the minimum cost using the conservation planning software Marxan. We examine three scenarios where the conservation targets of the agents differ. The first scenario (called NGO-NGO) models the situation where two NGOs are both are targeting different sets of threatened species. The second and third scenarios (called NGO-Gov and Gov-NGO, respectively) represent a case where a government agency attempts to implement a complementary conservation network representing all species, while an NGO is focused on achieving additional protection for the most endangered species. For each of these scenarios we examined three types of interactions between agents: i) acting in isolation where the agents are attempting to achieve their targets solely though their own actions ii) sharing information where each agent is aware of the species representation achieved within the other agent’s conservation network and, iii) pooling resources where agents combine their resources and undertake conservation actions as a single entity. The latter two interactions represent different types of collaborations and in each scenario we determine the cost savings from sharing information or pooling resources. In each case we examined the utility of these interactions from the viewpoint of the combined conservation network resulting from both agents' actions, as well as from each agent’s individual perspective. The costs for each agent to achieve their objectives varied depending on the order in which the agents acted, the type of interaction between agents, and the specific goals of each agent. There were significant cost savings from increased collaboration via sharing information in the NGO-NGO scenario were the agent’s representation goals were mutually exclusive (in terms of specie targeted). In the NGO-Gov and Gov-NGO scenarios, collaboration generated much smaller savings. If the two agents collaborate by pooling resources there are multiple ways the total cost could be shared between both agents. For each scenario we investigate the costs and benefits for all possible cost sharing proportions. We find that there are a range of cost sharing proportions where both agents can benefit in the NGO-NGO scenarios while the NGO-Gov and Gov-NGO scenarios again showed little benefit. Although the model presented here has a range of simplifying assumptions, it demonstrates that the value of collaboration can vary significantly in different situations. In most cases, collaborating would have associated costs and these costs need to be weighed against the potential benefits from collaboration. The model demonstrates a method for determining the range of collaboration costs that would result in collaboration providing an efficient use of scarce conservation resources.

Minimum description length, regularisation and multi-modal data

Relationships between clustering, description length, and regularisation are pointed out, motivating the introduction of a cost function with a description length interpretation and the unusual and useful property of having its minimum approximated by the densest mode of a distribution. A simple inverse kinematics example is used to demonstrate that this property can be used to select and learn one branch of a multi-valued mapping. This property is also used to develop a method for setting regularisation parameters according to the scale on which structure is exhibited in the training data. The regularisation technique is demonstrated on two real data sets, a classification problem and a regression problem.

Minimum description length, regularisation and multi-modal data

Conventional feed forward Neural Networks have used the sum-of-squares cost function for training. A new cost function is presented here with a description length interpretation based on Rissanen's Minimum Description Length principle. It is a heuristic that has a rough interpretation as the number of data points fit by the model. Not concerned with finding optimal descriptions, the cost function prefers to form minimum descriptions in a naive way for computational convenience. The cost function is called the Naive Description Length cost function. Finding minimum description models will be shown to be closely related to the identification of clusters in the data. As a consequence the minimum of this cost function approximates the most probable mode of the data rather than the sum-of-squares cost function that approximates the mean. The new cost function is shown to provide information about the structure of the data. This is done by inspecting the dependence of the error to the amount of regularisation. This structure provides a method of selecting regularisation parameters as an alternative or supplement to Bayesian methods. The new cost function is tested on a number of multi-valued problems such as a simple inverse kinematics problem. It is also tested on a number of classification and regression problems. The mode-seeking property of this cost function is shown to improve prediction in time series problems. Description length principles are used in a similar fashion to derive a regulariser to control network complexity.

Reductions of peak-to-average power ratio and optical beat interference in cost-effective OFDMA-PONs

The peak-to-average power ratio (PAPR) and optical beat interference (OBI) effects are examined thoroughly in orthogonal frequency-division multiplexing access (OFDMA)-passive optical networks (PONs) at a signal bit rate up to ∼ 20 Gb/s per channel using cost-effective intensity-modulation and direct-detection (IM/DD). Single-channel OOFDM and upstream multichannel OFDM-PONs are investigated for up to six users. A number of techniques for mitigating the PAPR and OBI effects are presented and evaluated including adaptive-loading algorithms such as bit/power-loading, clipping for PAPR reduction, and thermal detuning (TD) for the OBI suppression. It is shown that the bit-loading algorithm is a very efficient PAPR reduction technique by reducing it at about 1.2 dB over 100 Km of transmission. It is also revealed that the optimum method for suppressing the OBI is the TD + bit-loading. For a targeted BER of 1 × 10-3, the minimum allowed channel spacing is 11 GHz when employing six users. © 2013 Springer Science+Business Media New York.

Exploration of a simple, low cost, micro gas turbine recuperator solution for a domestic combined heat and power unit

For micro gas turbines (MGT) of around 1 kW or less, a commercially suitable recuperator must be used to produce a thermal efficiency suitable for use in UK Domestic Combined Heat and Power (DCHP). This paper uses computational fluid dynamics (CFD) to investigate a recuperator design based on a helically coiled pipe-in-pipe heat exchanger which utilises industry standard stock materials and manufacturing techniques. A suitable mesh strategy was established by geometrically modelling separate boundary layer volumes to satisfy y + near wall conditions. A higher mesh density was then used to resolve the core flow. A coiled pipe-in-pipe recuperator solution for a 1 kW MGT DCHP unit was established within the volume envelope suitable for a domestic wall-hung boiler. Using a low MGT pressure ratio (necessitated by using a turbocharger oil cooled journal bearing platform) meant unit size was larger than anticipated. Raising MGT pressure ratio from 2.15 to 2.5 could significantly reduce recuperator volume. Dimensional reasoning confirmed the existence of optimum pipe diameter combinations for minimum pressure drop. Maximum heat exchanger effectiveness was achieved using an optimum or minimum pressure drop pipe combination with large pipe length as opposed to a large pressure drop pipe combination with shorter pipe length. © 2011 Elsevier Ltd. All rights reserved.