The Cambridge Manufacturing Leaders' Programme

As with all Cambridge teaching, the Cambridge Manufacturing Leaders' Programme is based on one-to-one tutorial supervision, comprising guidance throughout a major strategic development project in the programme participant's company, interspersed with reflective study time spent in Cambridge. In this paper a description of the course is set in a wider philosophical context, looking at the role of work in a personal developmental sense, and the responsibility carried by manufacturing leaders for shaping and guiding that process. It is shown that the programme is rooted in and embodies important aspects of our European heritage regarding work as a learning process and the master/apprentice relationship as a way of giving educational guidance.

A novel method for rapid comparative quantitative analysis of nuclear fuel cycles

One of the greatest obstacles facing the nuclear industry is that of sustainability, both in terms of the finite reserves of uranium ore and the production of highly radiotoxic spent fuel which presents proliferation and environmental hazards. Alternative nuclear technologies have been suggested as a means of delivering enhanced sustainability with proposals including fast reactors, the use of thorium fuel and tiered fuel cycles. The debate as to which is the most appropriate technology continues, with each fuel system and reactor type delivering specific advantages and disadvantages which can be difficult to compare fairly. This paper demonstrates a framework of performance metrics which, coupled with a first-order lumped reactor model to determine nuclide population balances, can be used to quantify the aforementioned pros and cons for a range of different fuel and reactor combinations. The framework includes metrics such as fuel efficiency, spent fuel toxicity and proliferation resistance, and relative cycle performance is analysed through parallel coordinate plots, yielding a quantitative comparison of disparate cycles. © 2011 Elsevier Ltd. All rights reserved.

Comparison of manual and user guided methodologies for the classification and retrieval of construction site images

The amount of original imaging information produced yearly during the last decade has experienced a tremendous growth in all industries due to the technological breakthroughs in digital imaging and electronic storage capabilities. This trend is affecting the construction industry as well, where digital cameras and image databases are gradually replacing traditional photography. Owners demand complete site photograph logs and engineers store thousands of images for each project to use in a number of construction management tasks like monitoring an activity's progress and keeping evidence of the "as built" in case any disputes arise. So far, retrieval methodologies are done manually with the user being responsible for imaging classification according to specific rules that serve a limited number of construction management tasks. New methods that, with the guidance of the user, can automatically classify and retrieve construction site images are being developed and promise to remove the heavy burden of manually indexing images. In this paper, both the existing methods and a novel image retrieval method developed by the authors for the classification and retrieval of construction site images are described and compared. Specifically a number of examples are deployed in order to present their advantages and limitations. The results from this comparison demonstrates that the content based image retrieval method developed by the authors can reduce the overall time spent for the classification and retrieval of construction images while providing the user with the flexibility to retrieve images according different classification schemes.

Testing of Depth-Encoded Hough Voting for Infrastructure Object Detection

The lack of viable methods to map and label existing infrastructure is one of the engineering grand challenges for the 21st century. For instance, over two thirds of the effort needed to geometrically model even simple infrastructure is spent on manually converting a cloud of points to a 3D model. The result is that few facilities today have a complete record of as-built information and that as-built models are not produced for the vast majority of new construction and retrofit projects. This leads to rework and design changes that can cost up to 10% of the installed costs. Automatically detecting building components could address this challenge. However, existing methods for detecting building components are not view and scale-invariant, or have only been validated in restricted scenarios that require a priori knowledge without considering occlusions. This leads to their constrained applicability in complex civil infrastructure scenes. In this paper, we test a pose-invariant method of labeling existing infrastructure. This method simultaneously detects objects and estimates their poses. It takes advantage of a recent novel formulation for object detection and customizes it to generic civil infrastructure scenes. Our preliminary experiments demonstrate that this method achieves convincing recognition results.

Sparsity-Inducing Optimization Algorithm for the Extraction of Planar Structures in Noisy Point-Cloud Data

Most of the manual labor needed to create the geometric building information model (BIM) of an existing facility is spent converting raw point cloud data (PCD) to a BIM description. Automating this process would drastically reduce the modeling cost. Surface extraction from PCD is a fundamental step in this process. Compact modeling of redundant points in PCD as a set of planes leads to smaller file size and fast interactive visualization on cheap hardware. Traditional approaches for smooth surface reconstruction do not explicitly model the sparse scene structure or significantly exploit the redundancy. This paper proposes a method based on sparsity-inducing optimization to address the planar surface extraction problem. Through sparse optimization, points in PCD are segmented according to their embedded linear subspaces. Within each segmented part, plane models can be estimated. Experimental results on a typical noisy PCD demonstrate the effectiveness of the algorithm.

Content Based Integration of Construction Site Images in AEC/FM Model Based Systems

The Architecture, Engineering, Construction and Facilities Management (AEC/FM) industry is rapidly becoming a multidisciplinary, multinational and multi-billion dollar economy, involving large numbers of actors working concurrently at different locations and using heterogeneous software and hardware technologies. Since the beginning of the last decade, a great deal of effort has been spent within the field of construction IT in order to integrate data and information from most computer tools used to carry out engineering projects. For this purpose, a number of integration models have been developed, like web-centric systems and construction project modeling, a useful approach in representing construction projects and integrating data from various civil engineering applications. In the modern, distributed and dynamic construction environment it is important to retrieve and exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research demonstrated that a major hurdle in AEC/FM data integration in such systems is caused by its variety of data types and that a significant part of the data is stored in semi-structured or unstructured formats. Therefore, new integrative approaches are needed to handle non-structured data types like images and text files. This research is focused on the integration of construction site images. These images are a significant part of the construction documentation with thousands stored in site photographs logs of large scale projects. However, locating and identifying such data needed for the important decision making processes is a very hard and time-consuming task, while so far, there are no automated methods for associating them with other related objects. Therefore, automated methods for the integration of construction images are important for construction information management. During this research, processes for retrieval, classification, and integration of construction images in AEC/FM model based systems have been explored. Specifically, a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval have been deployed in order to develop a methodology for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks.

Coupled neutronic thermo-hydraulic analysis of full PWR core with Monte-Carlo based BGCore system

BGCore reactor analysis system was recently developed at Ben-Gurion University for calculating in-core fuel composition and spent fuel emissions following discharge. It couples the Monte Carlo transport code MCNP with an independently developed burnup and decay module SARAF. Most of the existing MCNP based depletion codes (e.g. MOCUP, Monteburns, MCODE) tally directly the one-group fluxes and reaction rates in order to prepare one-group cross sections necessary for the fuel depletion analysis. BGCore, on the other hand, uses a multi-group (MG) approach for generation of one group cross-sections. This coupling approach significantly reduces the code execution time without compromising the accuracy of the results. Substantial reduction in the BGCore code execution time allows consideration of problems with much higher degree of complexity, such as introduction of thermal hydraulic (TH) feedback into the calculation scheme. Recently, a simplified TH feedback module, THERMO, was developed and integrated into the BGCore system. To demonstrate the capabilities of the upgraded BGCore system, a coupled neutronic TH analysis of a full PWR core was performed. The BGCore results were compared with those of the state of the art 3D deterministic nodal diffusion code DYN3D (Grundmann et al.; 2000). Very good agreement in major core operational parameters including k-eff eigenvalue, axial and radial power profiles, and temperature distributions between the BGCore and DYN3D results was observed. This agreement confirms the consistency of the implementation of the TH feedback module. Although the upgraded BGCore system is capable of performing both, depletion and TH analyses, the calculations in this study were performed for the beginning of cycle state with pre-generated fuel compositions. © 2011 Published by Elsevier B.V.

The potential use of 241Am as proliferation resistant burnable poison in PWRs

This paper discusses the use of 241Am as proliferation resistant burnable poison for light water reactors. Homogeneous addition of small (as little as 0.12%) amounts of 241Am to the conventional light water reactor fuel results in significant increase in 238Pu/Pu ratio in the discharged fuel improving its proliferation resistance. Moreover, 241Am, admixed to the fuel, acts as burnable absorber allowing for substantial reduction in conventional reactivity control means without a notable fuel cycle length penalty. This is possible due to favorable characteristics of 241Am transmutation chain. The fuel cycle length penalty of introducing 241Am into the core is evaluated and discussed, as well as the impact of He production in the fuel pins and degradation of reactivity feedback coefficients. Proliferation resistance and reactivity control features related to the use of 241Am are compared to those of using 237Np, which has also been suggested as an additive to the conventional fuel in order to improve its proliferation resistance. It was found that 241Am admixture is more favorable than 237Np admixture because of the smaller fuel cycle length penalty and higher burnable poison savings. Addition of either 237Np or 241Am would provide substantial but not ultimate protection from misuse of Pu originating in the spent fuel from the commercial power reactors. Therefore, the benefits from application of the concept would have to be carefully evaluated against the additional costs and proliferation risks associated with manufacturing of 237Np or 241Am doped fuel. Although this work concerns specifically with PWRs, the conclusions could also be applied to BWRs and, to some extent, to other thermal spectrum reactor types. © 2009 Elsevier Ltd. All rights reserved.

Effect of95 241Am(n, γ) reaction branching ratio on fuel cycle and reactor design characteristics

The growing interest in innovative reactors and advanced fuel cycle designs requires more accurate prediction of various transuranic actinide concentrations during irradiation or following discharge because of their effect on reactivity or spent-fuel emissions, such as gamma and neutron activity and decay heat. In this respect, many of the important actinides originate from the 241Am(n,γ) reaction, which leads to either the ground or the metastable state of 242Am. The branching ratio for this reaction depends on the incident neutron energy and has very large uncertainty in the current evaluated nuclear data files. This study examines the effect of accounting for the energy dependence of the 241Am(n,γ) reaction branching ratio calculated from different evaluated data files for different reactor and fuel types on the reactivity and concentrations of some important actinides. The results of the study confirm that the uncertainty in knowing the 241Am(n,γ) reaction branching ratio has a negligible effect on the characteristics of conventional light water reactor fuel. However, in advanced reactors with large loadings of actinides in general, and 241Am in particular, the branching ratio data calculated from the different data files may lead to significant differences in the prediction of the fuel criticality and isotopic composition. Moreover, it was found that neutron energy spectrum weighting of the branching ratio in each analyzed case is particularly important and may result in up to a factor of 2 difference in the branching ratio value. Currently, most of the neutronic codes have a single branching ratio value in their data libraries, which is sometimes difficult or impossible to update in accordance with the neutron spectrum shape for the analyzed system.

Implementation of multi-group cross-section methodology in BGCore MC-depletion code

BGCore is a software package for comprehensive computer simulation of nuclear reactor systems and their fuel cycles. The BGCore interfaces Monte Carlo particles transport code MCNP4C with a SARAF module - an independently developed code for calculating in-core fuel composition and spent fuel emissions following discharge. In BGCore system, depletion coupling methodology is based on the multi-group approach that significantly reduces computation time and allows tracking of large number of nuclides during calculations. In this study, burnup calculation capabilities of BGCore system were validated against well established and verified, computer codes for thermal and fast spectrum lattices. Very good agreement in k eigenvalue and nuclide densities prediction was observed for all cases under consideration. In addition, decay heat prediction capabilities of the BGCore system were benchmarked against the most recent edition of ANS Standard methodology for UO2 fuel decay power prediction in LWRs. It was found that the difference between ANS standard data and that predicted by the BGCore does not exceed 5%.

Assessment of homogeneous thorium/uranium fuel for pressurized water reactors

The homogeneous ThO2-UO2 fuel cycle option for a pressurized water reactor (PWR) of current technology is investigated. The fuel cycle assessment was carried out by calculating the main performance parameters: natural uranium and separative work requirements, fuel cycle cost, and proliferation potential of the spent fuel. These performance parameters were compared with a corresponding slightly enriched (all-U) fuel cycle applied to a PWR of current technology. The main conclusion derived from this comparison is that fuel cycle requirements and fuel cycle cost for the mixed Th/U fuel are higher in comparison with those of the all-U fuel. A comparison and analysis of the quantity and isotopic composition of discharged Pu indicate that the Th/U fuel cycle provides only a moderate improvement of the proliferation resistance. Thus, the overall conclusion of the investigation is that there is no economic justification to introduce Th into a light water reactor fuel cycle as a homogeneous ThO2-UO2 mixture.

Sensitivity analysis and optimization of the nuclear fuel cycle

A sensitivity study has been conducted to assess the robustness of the conclusions presented in the MIT Fuel Cycle Study. The Once Through Cycle (OTC) is considered as the base-line case, while advanced technologies with fuel recycling characterize the alternative fuel cycles. The options include limited recycling in LWRs and full recycling in fast reactors and in high conversion LWRs. Fast reactor technologies studied include both oxide and metal fueled reactors. The analysis allowed optimization of the fast reactor conversion ratio with respect to desired fuel cycle performance characteristics. The following parameters were found to significantly affect the performance of recycling technologies and their penetration over time: Capacity Factors of the fuel cycle facilities, Spent Fuel Cooling Time, Thermal Reprocessing Introduction Date, and incore and Out-of-core TRU Inventory Requirements for recycling technology. An optimization scheme of the nuclear fuel cycle is proposed. Optimization criteria and metrics of interest for different stakeholders in the fuel cycle (economics, waste management, environmental impact, etc.) are utilized for two different optimization techniques (linear and stochastic). Preliminary results covering single and multi-variable and single and multi-objective optimization demonstrate the viability of the optimization scheme.

Effects of cooling time on a closed LWR fuel cycle

In this study, the effects of cooling time prior to reprocessing spent LWR fuel has on the reactor physics characteristics of a PWR fully loaded with homogeneously mixed U-Pu or U-TRU oxide (MOX) fuel is examined. A reactor physics analysis was completed using the CASM04e code. A void reactivity feedback coefficient analysis was also completed for an infinite lattice of fresh fuel assemblies. Some useful conclusions can be made regarding the effect that cooling time prior to reprocessing spent LWR fuel has on a closed homogeneous MOX fuel cycle. The computational analysis shows that it is more neutronically efficient to reprocess cooled spent fuel into homogeneous MOX fuel rods earlier rather than later as the fissile fuel content decreases with time. Also, the number of spent fuel rods needed to fabricate one MOX fuel rod increases as cooling time increases. In the case of TRU MOX fuel, with time, there is an economic tradeoff between fuel handling difficulty and higher throughput of fuel to be reprocessed. The void coefficient analysis shows that the void coefficient becomes progressively more restrictive on fuel Pu content with increasing spent fuel cooling time before reprocessing.

A survey of alternative once-through fast reactor core designs

Reprocessing of Light Water Reactor (LWR) spent fuel to recover plutonium or transuranics for use in Sodium cooled Fast Reactors (SFRs) is a distant prospect in the U.S.A. This has motivated our evaluation of potentially cost-effective operation of uranium startup fast reactors (USFRs) in a once-through mode. This review goes beyond findings reported earlier based on a UC fueled MgO reflected SFR to describe a broader parametric study of options. Cores were evaluated for a variety of fuel/coolant/reflector combinations: UC/UZr/UO 2/UN;Na/Pb; MgO/SS/Zr. The challenge is achieving high burnup while minimizing enrichment and respecting both cladding fluence/dpa and reactivity lifetime limits. These parametric studies show that while UC fuel is still the leading contender, UO 2 fuel and ZrH 1.7 moderated metallic fuel are also attractive if UC proves to be otherwise inadequate. Overall, these findings support the conclusion that a competitive fuel cycle cost and uranium utilization compared to LWRs is possible for SFRs operated on a once-through uranium fueled fuel cycle. In addition, eventual transition to TRU recycle mode is studied, as is a small test reactor to demonstrate key features.

Thorium fuel cycles for light water reactors: homogeneous design

The proliferation potential of the present light water reactor (LWR) fuel cycle is related primarily to the quantity and the quality of the residual Pu contained in the spent-fuel stockpile, although other potentially “weapons usable” materials are also a concern. Thorium-based nuclear fuel produces much smaller amounts of Pu in comparison with standard LWR fuel, and consequently, it is more proliferation resistant than conventional slightly enriched all-U fuel; the long-term toxicity of the spent-fuel stockpile is also reduced