An Innovative Crop-Forage Intercrop System: Early Cycle Soybean Cultivars and Palisadegrass

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Economic and technical feasibility study of a combined-cycle cogeneration system associated with cellulose plants

In this paper, is presented an economical and technical feasibility study of a combined cycle cogeneration system proposed to be used in a pulp plant located in Brazil, where around 95% of country's pulp production is done by the use of Kraft Process. This process allows the use of black liquor and other by-products as fuel. This study is based upon actual data from a pulp plant with a daily production of 1000 tons., that generates part of the energy demanded by the process in a conventional cogeneration system with condensing steam turbine and two extractions. The addition of a gas turbine was studied to compare electricity production level and its related costs between original system and the new one, considering that the former can use industrial by-products and firewood as fuel, when required. Several parameters related to electric generation systems operation and production costs were studied. The use of natural gas in the combined cycle, in comparison with the use of firewood in the conventional system was studied. The advantages of natural gas fuel are highlighted. The surplus availability and the electricity generation costs are presented as a function of pulp and black liquor production.

Quantitative cell-cycle protein expression in oral cancer assessed by computer-assisted system

The knowledge of cell-cycle control has shown that the capacity of malignant growth is acquired by the stepwise accumulation of defects in specific genes regulating cell growth. Histologic diagnosis might be improved by a quantitative evaluation of more specific diagnosis biomarkers, which could help to precisely identify pre-malignant and malignant oral lesions. The aim of the present study is to evaluate whether computer-based quantitative assessment of p53, PCNA and Ki-67 immunohistochemical expression, could be used clinically to foresee the risk of oral malignant transformation. This retrospective study was carried out in ninety-five oral biopsies, 27 were classified as fibrous inflammatory hyperplasia, 40 as leukoplakia and 28 as oral squamous cell carcinoma. Sixteen out of the 40 leukoplakia were diagnosed as non-dysplastic leukoplakia, the other 24 being dysplastic leukoplakia, of which 50.0% were classified as moderate to severe dysplasia. Comparison of the four groups of oral tissues showed significant rises in p53 and Ki-67 positivity index, which increased steadily in the order benign, pre-malignant, and malignant. In contrast, it was not possible to relate higher PCNA levels with pre-malignant and malignant oral lesions. We therefore conclude that PCNA immunohistochemistry expression is probably an inappropriate marker to identify oral carcinogenesis, whereas joint quantitative evaluation of p53 and Ki-67, appears to be useful as a tumor marker, providing a pre-diagnostic estimate of the potential for cell-cycle deregulation of the oral proliferate status.

An ultrasensitive NanoLuc-based luminescence system for monitoring Plasmodium berghei throughout its life cycle

BACKGROUND: Bioluminescence imaging is widely used for cell-based assays and animal imaging studies, both in biomedical research and drug development. Its main advantages include its high-throughput applicability, affordability, high sensitivity, operational simplicity, and quantitative outputs. In malaria research, bioluminescence has been used for drug discovery in vivo and in vitro, exploring host-pathogen interactions, and studying multiple aspects of Plasmodium biology. While the number of fluorescent proteins available for imaging has undergone a great expansion over the last two decades, enabling simultaneous visualization of multiple molecular and cellular events, expansion of available luciferases has lagged behind. The most widely used bioluminescent probe in malaria research is the Photinus pyralis firefly luciferase, followed by the more recently introduced Click-beetle and Renilla luciferases. Ultra-sensitive imaging of Plasmodium at low parasite densities has not been previously achieved. With the purpose of overcoming these challenges, a Plasmodium berghei line expressing the novel ultra-bright luciferase enzyme NanoLuc, called PbNLuc has been generated, and is presented in this work. RESULTS: NanoLuc shows at least 150 times brighter signal than firefly luciferase in vitro, allowing single parasite detection in mosquito, liver, and sexual and asexual blood stages. As a proof-of-concept, the PbNLuc parasites were used to image parasite development in the mosquito, liver and blood stages of infection, and to specifically explore parasite liver stage egress, and pre-patency period in vivo. CONCLUSIONS: PbNLuc is a suitable parasite line for sensitive imaging of the entire Plasmodium life cycle. Its sensitivity makes it a promising line to be used as a reference for drug candidate testing, as well as the characterization of mutant parasites to explore the function of parasite proteins, host-parasite interactions, and the better understanding of Plasmodium biology. Since the substrate requirements of NanoLuc are different from those of firefly luciferase, dual bioluminescence imaging for the simultaneous characterization of two lines, or two separate biological processes, is possible, as demonstrated in this work.

Sistema de simulación de escenarios de ciclos avanzados de combustible nuclear en transición = Simulation system for advanced fuel cycle transition scenarios

El estudio de los ciclos del combustible nuclear requieren de herramientas computacionales o "códigos" versátiles para dar respuestas al problema multicriterio de evaluar los actuales ciclos o las capacidades de las diferentes estrategias y escenarios con potencial de desarrollo en a nivel nacional, regional o mundial. Por otra parte, la introducción de nuevas tecnologías para reactores y procesos industriales hace que los códigos existentes requieran nuevas capacidades para evaluar la transición del estado actual del ciclo del combustible hacia otros más avanzados y sostenibles. Brevemente, esta tesis se centra en dar respuesta a las principales preguntas, en términos económicos y de recursos, al análisis de escenarios de ciclos de combustible, en particular, para el análisis de los diferentes escenarios del ciclo del combustible de relativa importancia para España y Europa. Para alcanzar este objetivo ha sido necesaria la actualización y el desarrollo de nuevas capacidades del código TR_EVOL (Transition Evolution code). Este trabajo ha sido desarrollado en el Programa de Innovación Nuclear del CIEMAT desde el año 2010. Esta tesis se divide en 6 capítulos. El primer capítulo ofrece una visión general del ciclo de combustible nuclear, sus principales etapas y los diferentes tipos utilizados en la actualidad o en desarrollo para el futuro. Además, se describen las fuentes de material nuclear que podrían ser utilizadas como combustible (uranio y otros). También se puntualizan brevemente una serie de herramientas desarrolladas para el estudio de estos ciclos de combustible nuclear. El capítulo 2 está dirigido a dar una idea básica acerca de los costes involucrados en la generación de electricidad mediante energía nuclear. Aquí se presentan una clasificación de estos costos y sus estimaciones, obtenidas en la bibliografía, y que han sido evaluadas y utilizadas en esta tesis. Se ha incluido también una breve descripción del principal indicador económico utilizado en esta tesis, el “coste nivelado de la electricidad”. El capítulo 3 se centra en la descripción del código de simulación desarrollado para el estudio del ciclo del combustible nuclear, TR_EVOL, que ha sido diseñado para evaluar diferentes opciones de ciclos de combustibles. En particular, pueden ser evaluados las diversos reactores con, posiblemente, diferentes tipos de combustibles y sus instalaciones del ciclo asociadas. El módulo de evaluaciones económica de TR_EVOL ofrece el coste nivelado de la electricidad haciendo uso de las cuatro fuentes principales de información económica y de la salida del balance de masas obtenido de la simulación del ciclo en TR_EVOL. Por otra parte, la estimación de las incertidumbres en los costes también puede ser efectuada por el código. Se ha efectuado un proceso de comprobación cruzada de las funcionalidades del código y se descrine en el Capítulo 4. El proceso se ha aplicado en cuatro etapas de acuerdo con las características más importantes de TR_EVOL, balance de masas, composición isotópica y análisis económico. Así, la primera etapa ha consistido en el balance masas del ciclo de combustible nuclear actual de España. La segunda etapa se ha centrado en la comprobación de la composición isotópica del flujo de masas mediante el la simulación del ciclo del combustible definido en el proyecto CP-ESFR UE. Las dos últimas etapas han tenido como objetivo validar el módulo económico. De este modo, en la tercera etapa han sido evaluados los tres principales costes (financieros, operación y mantenimiento y de combustible) y comparados con los obtenidos por el proyecto ARCAS, omitiendo los costes del fin del ciclo o Back-end, los que han sido evaluado solo en la cuarta etapa, haciendo uso de costes unitarios y parámetros obtenidos a partir de la bibliografía. En el capítulo 5 se analizan dos grupos de opciones del ciclo del combustible nuclear de relevante importancia, en términos económicos y de recursos, para España y Europa. Para el caso español, se han simulado dos grupos de escenarios del ciclo del combustible, incluyendo estrategias de reproceso y extensión de vida de los reactores. Este análisis se ha centrado en explorar las ventajas y desventajas de reprocesado de combustible irradiado en un país con una “relativa” pequeña cantidad de reactores nucleares. Para el grupo de Europa se han tratado cuatro escenarios, incluyendo opciones de transmutación. Los escenarios incluyen los reactores actuales utilizando la tecnología reactor de agua ligera y ciclo abierto, un reemplazo total de los reactores actuales con reactores rápidos que queman combustible U-Pu MOX y dos escenarios del ciclo del combustible con transmutación de actínidos minoritarios en una parte de los reactores rápidos o en sistemas impulsados por aceleradores dedicados a transmutación. Finalmente, el capítulo 6 da las principales conclusiones obtenidas de esta tesis y los trabajos futuros previstos en el campo del análisis de ciclos de combustible nuclear. ABSTRACT The study of the nuclear fuel cycle requires versatile computational tools or “codes” to provide answers to the multicriteria problem of assessing current nuclear fuel cycles or the capabilities of different strategies and scenarios with potential development in a country, region or at world level. Moreover, the introduction of new technologies for reactors and industrial processes makes the existing codes to require new capabilities to assess the transition from current status of the fuel cycle to the more advanced and sustainable ones. Briefly, this thesis is focused in providing answers to the main questions about resources and economics in fuel cycle scenario analyses, in particular for the analysis of different fuel cycle scenarios with relative importance for Spain and Europe. The upgrade and development of new capabilities of the TR_EVOL code (Transition Evolution code) has been necessary to achieve this goal. This work has been developed in the Nuclear Innovation Program at CIEMAT since year 2010. This thesis is divided in 6 chapters. The first one gives an overview of the nuclear fuel cycle, its main stages and types currently used or in development for the future. Besides the sources of nuclear material that could be used as fuel (uranium and others) are also viewed here. A number of tools developed for the study of these nuclear fuel cycles are also briefly described in this chapter. Chapter 2 is aimed to give a basic idea about the cost involved in the electricity generation by means of the nuclear energy. The main classification of these costs and their estimations given by bibliography, which have been evaluated in this thesis, are presented. A brief description of the Levelized Cost of Electricity, the principal economic indicator used in this thesis, has been also included. Chapter 3 is focused on the description of the simulation tool TR_EVOL developed for the study of the nuclear fuel cycle. TR_EVOL has been designed to evaluate different options for the fuel cycle scenario. In particular, diverse nuclear power plants, having possibly different types of fuels and the associated fuel cycle facilities can be assessed. The TR_EVOL module for economic assessments provides the Levelized Cost of Electricity making use of the TR_EVOL mass balance output and four main sources of economic information. Furthermore, uncertainties assessment can be also carried out by the code. A cross checking process of the performance of the code has been accomplished and it is shown in Chapter 4. The process has been applied in four stages according to the most important features of TR_EVOL. Thus, the first stage has involved the mass balance of the current Spanish nuclear fuel cycle. The second stage has been focused in the isotopic composition of the mass flow using the fuel cycle defined in the EU project CP-ESFR. The last two stages have been aimed to validate the economic module. In the third stage, the main three generation costs (financial cost, O&M and fuel cost) have been assessed and compared to those obtained by ARCAS project, omitting the back-end costs. This last cost has been evaluated alone in the fourth stage, making use of some unit cost and parameters obtained from the bibliography. In Chapter 5 two groups of nuclear fuel cycle options with relevant importance for Spain and Europe are analyzed in economic and resources terms. For the Spanish case, two groups of fuel cycle scenarios have been simulated including reprocessing strategies and life extension of the current reactor fleet. This analysis has been focused on exploring the advantages and disadvantages of spent fuel reprocessing in a country with relatively small amount of nuclear power plants. For the European group, four fuel cycle scenarios involving transmutation options have been addressed. Scenarios include the current fleet using Light Water Reactor technology and open fuel cycle, a full replacement of the initial fleet with Fast Reactors burning U-Pu MOX fuel and two fuel cycle scenarios with Minor Actinide transmutation in a fraction of the FR fleet or in dedicated Accelerator Driven Systems. Finally, Chapter 6 gives the main conclusions obtained from this thesis and the future work foreseen in the field of nuclear fuel cycle analysis.

Development of a conceptual model of the soil-moisture-plant sub-system of the hydrological cycle

The soil-plant-moisture subsystem is an important component of the hydrological cycle. Over the last 20 or so years a number of computer models of varying complexity have represented this subsystem with differing degrees of success. The aim of this present work has been to improve and extend an existing model. The new model is less site specific thus allowing for the simulation of a wide range of soil types and profiles. Several processes, not included in the original model, are simulated by the inclusion of new algorithms, including: macropore flow; hysteresis and plant growth. Changes have also been made to the infiltration, water uptake and water flow algorithms. Using field data from various sources, regression equations have been derived which relate parameters in the suction-conductivity-moisture content relationships to easily measured soil properties such as particle-size distribution data. Independent tests have been performed on laboratory data produced by Hedges (1989). The parameters found by regression for the suction relationships were then used in equations describing the infiltration and macropore processes. An extensive literature review produced a new model for calculating plant growth from actual transpiration, which was itself partly determined by the root densities and leaf area indices derived by the plant growth model. The new infiltration model uses intensity/duration curves to disaggregate daily rainfall inputs into hourly amounts. The final model has been calibrated and tested against field data, and its performance compared to that of the original model. Simulations have also been carried out to investigate the effects of various parameters on infiltration, macropore flow, actual transpiration and plant growth. Qualitatively comparisons have been made between these results and data given in the literature.

A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle

Acknowledgements. This work was mainly funded by the EU FP7 CARBONES project (contracts FP7-SPACE-2009-1-242316), with also a small contribution from GEOCARBON project (ENV.2011.4.1.1-1-283080). This work used eddy covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program; DE-FG02-04ER63917 and DE-FG02-04ER63911), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), GreenGrass, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia, USCCC. We acknowledge the financial support to the eddy covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, Max Planck Institute for Biogeochemistry, National Science Foundation, University of Tuscia, Université Laval and Environment Canada and US Department of Energy and the database development and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, University of California-Berkeley, University of Virginia. Philippe Ciais acknowledges support from the European Research Council through Synergy grant ERC-2013-SyG-610028 “IMBALANCE-P”. The authors wish to thank M. Jung for providing access to the GPP MTE data, which were downloaded from the GEOCARBON data portal (https://www.bgc-jena.mpg.de/geodb/projects/Data.php). The authors are also grateful to computing support and resources provided at LSCE and to the overall ORCHIDEE project that coordinate the development of the code (http://labex.ipsl.fr/orchidee/index.php/about-the-team).

A framework for fully decentralised cycle stealing

Ordinary desktop computers continue to obtain ever more resources – in-creased processing power, memory, network speed and bandwidth – yet these resources spend much of their time underutilised. Cycle stealing frameworks harness these resources so they can be used for high-performance computing. Traditionally cycle stealing systems have used client-server based architectures which place significant limits on their ability to scale and the range of applica-tions they can support. By applying a fully decentralised network model to cycle stealing the limits of centralised models can be overcome. Using decentralised networks in this manner presents some difficulties which have not been encountered in their previous uses. Generally decentralised ap-plications do not require any significant fault tolerance guarantees. High-performance computing on the other hand requires very stringent guarantees to ensure correct results are obtained. Unfortunately mechanisms developed for traditional high-performance computing cannot be simply translated because of their reliance on a reliable storage mechanism. In the highly dynamic world of P2P computing this reliable storage is not available. As part of this research a fault tolerance system has been created which provides considerable reliability without the need for a persistent storage. As well as increased scalability, fully decentralised networks offer the ability for volunteers to communicate directly. This ability provides the possibility of supporting applications whose tasks require direct, message passing style communication. Previous cycle stealing systems have only supported embarrassingly parallel applications and applications with limited forms of communication so a new programming model has been developed which can support this style of communication within a cycle stealing context. In this thesis I present a fully decentralised cycle stealing framework. The framework addresses the problems of providing a reliable fault tolerance sys-tem and supporting direct communication between parallel tasks. The thesis includes a programming model for developing cycle stealing applications with direct inter-process communication and methods for optimising object locality on decentralised networks.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Demonstration of Software Agents Prototype System : [AIMM] Agents for Improving Maintenance Management

This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. • Refining the development of a multi agent system for data mining in virtual environments (Active Worlds) by developing and implementing a filtering agent on the results obtained from applying data mining techniques on the maintenance data. • Integrating the filtering agent within the multi agents system in an interactive networked multi-user 3D virtual environment. • Populating maintenance data and discovering new rules of knowledge.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

HVAC system size – getting it right

There is evidence that many heating, ventilating & air conditioning (HVAC) systems, installed in larger buildings, have more capacity than is ever required to keep the occupants comfortable. This paper explores the reasons why this can occur, by examining a typical brief/design/documentation process. Over-sized HVAC systems cost more to install and operate and may not be able to control thermal comfort as well as a “right-sized” system. These impacts are evaluated, where data exists. Finally, some suggestions are developed to minimise both the extent of, and the negative impacts of, HVAC system over-sizing, for example: • Challenge “rules of thumb” and/or brief requirements which may be out of date. • Conduct an accurate load estimate, using AIRAH design data, specific to project location, and then resist the temptation to apply “safety factors • Use a load estimation program that accounts for thermal storage and diversification of peak loads for each zone and air handling system. • Select chiller sizes and staged or variable speed pumps and fans to ensure good part load performance. • Allow for unknown future tenancies by designing flexibility into the system, not by over-sizing. For example, generous sizing of distribution pipework and ductwork will allow available capacity to be redistributed. • Provide an auxiliary tenant condenser water loop to handle high load areas. • Consider using an Integrated Design Process, build an integrated load and energy use simulation model and test different operational scenarios • Use comprehensive Life Cycle Cost analysis for selection of the most optimal design solutions. This paper is an interim report on the findings of CRC-CI project 2002-051-B, Right-Sizing HVAC Systems, which is due for completion in January 2006.

Decision support system architecture for consultant selection

Decision Support System (DSS) has played a significant role in construction project management. This has been proven that a lot of DSS systems have been implemented throughout the whole construction project life cycle. However, most research only concentrated in model development and left few fundamental aspects in Information System development. As a result, the output of researches are complicated to be adopted by lay person particularly those whom come from a non-technical background. Hence, a DSS should hide the abstraction and complexity of DSS models by providing a more useful system which incorporated user oriented system. To demonstrate a desirable architecture of DSS particularly in public sector planning, we aim to propose a generic DSS framework for consultant selection. It will focus on the engagement of engineering consultant for irrigation and drainage infrastructure. The DSS framework comprise from operational decision to strategic decision level. The expected result of the research will provide a robust framework of DSS for consultant selection. In addition, the paper also discussed other issues that related to the existing DSS framework by integrating enabling technologies from computing. This paper is based on the preliminary case study conducted via literature review and archival documents at Department of Irrigation and Drainage (DID) Malaysia. The paper will directly affect to the enhancement of consultant pre-qualification assessment and selection tools. By the introduction of DSS in this area, the selection process will be more efficient in time, intuitively aided qualitative judgment, and transparent decision through aggregation of decision among stakeholders.