16 research outputs found
Mass action models of Falklands War battles
No full textWe develop a dataset describing variables associated with six Falklands War battles: combatant numbers; deaths; temporal aspects; and offensive support. Linear relationships between battle duration and deaths necessitate using force and loss ratios to remove temporal variation. Mass action models of battle attrition fit this dataset poorly (at best coefficient of determination ). The low level rules in simulations used by military force designers frequently share assumptions with, or are, mass action models. Errors in force balance or constitution are dangerous so exposing problems with and exploring improvements on existing combat models is important. While six data points are too few for a thorough analysis, our results are consistent with: a linear relationship between time in danger and number killed; different times in danger for the two sides, dependent on detection and lethality ranges; and data substructure, even when temporal aspects are removed through ratio models. This data substructure indicates at least one extra variable needs to be considered. We contend that this variable is related to suppression, and this contention is not falsified by the high use of offensive support in the most successful attacks. Mathematical modellers should consider cancelling out temporal variation in combat datasets through ratio models and/or exploring the effects of mutable detection and lethality ranges. Suppression is an attempt to manage exposure to death, to introduce non-stationarity and irregularity into the dataset to benefit the suppressor, to change the bounds of the system using a soft controller; we should investigate how to model it. Force designers should ask simulation modellers whether the mathematical models underlying their simulations represent suppression accurately (or at all) and rethink reductions of simultaneously delivered offensive support available on demand based on models ignoring suppression.
References J. B. A. Bailey. Field artillery and firepower. Routledge, London, 2009. A. Baudry. La Bataille navale: etudes sur les facteurs tactiques. 1912. Translated by C. F. Atkinson. The naval battle: Studies of the tactical factors. Hugh Rees, London, 1914. http://gallica.bnf.fr/ark:/12148/bpt6k11639411/f9.image S. Biddle. Military power: Explaining victory and defeat in modern battle. Princeton University Press, Princeton, New Jersey, 2004. F. D. J. Bowden, B. M. Pincombe and P. B. Williams. Feasible scenario spaces: A new way of measuring capability impacts. In T. Weber, M. J. McPhee and R. S. Anderssen (eds), MODSIM2015, 836–842, 2015. http://www.mssanz.org.au/modsim2015/D3/bowden.pdf D. Brown. The Royal Navy and the Falklands War. Pen and Sword Books, Barnsley, UK, 1987. J. V. Chase. Sea fights: A mathematical investigation of the effect of superiority of force in combats upon the sea. Naval War College Archives, RG 8, Box 109, XTAV (1902), 1902. A. J. Echevarria. After Clausewitz: German military thinkers before the Great War. University Press of Kansas, Lawrence, KS, USA, 2001. J. A. English and B. I. Gudmundsson. On infantry. Praeger, Westport, CT, USA, 1994. B. A. Fiske. American Naval Policy. U.S. Naval Institute Proceedings, January 1905. L. Freedman. The official history of the Falklands Campaign, Volume 2: War and diplomacy. Routledge, London, 2005. G. Fremont-Barnes. The Falklands 1982: Ground operations in the South Atlantic. Osprey, Oxford, UK, 2012. https://ospreypublishing.com/the-falklands-2130 S. Fitz-Gibbon. Not mentioned in despatches: The history and mythology of the Battle of Goose Green. The Lutterworth Press, Cambridge, UK, 1995. http://www.lutterworth.com/product_info.php/products_id/1019 T. R. Hogan. No shells, no attack! The use of fire support by three Commando Brigade Royal Marines during the 1982 Falkland Islands War. AD-A208862, US Army War College, PA, USA, 1989. http://www.dtic.mil/dtic/tr/fulltext/u2/a208862.pdf. L. R. Kosowski, A. Pincombe and B. Pincombe. Irrelevance of the fractal dimension term in the modified fractal attrition equation. ANZIAM J, 52:C988–C1011, 2011. doi:10.21914/anziamj.v52i0.3963 F. W. Lanchester. Aircraft in warfare: The dawn of the fourth arm. Constable, London, 1916. https://archive.org/details/aircraftinwarfar00lancrich C. D. Landry. British artillery during Operation Corporate. Masters Thesis, United States Marine Corps Command and Staff College, 2002. http://www.dtic.mil/dtic/tr/fulltext/u2/a401278.pdf. T. W. Lucas and T. Turkes. Fitting Lanchester equations to the Battles of Kursk and Ardennes. Nav. Res. Log., 51:95–116, 2004. doi:10.1002/nav.10101 J. Millikan, M. Wong and D. Grieger. Suppression of dismounted soldiers: Towards improving dynamic threat assessment in closed loop combat simulations. In J. Piantadosi, R. S. Anderssen and J. Boland (eds), MODSIM2013, 1054–1060, 2013. http://www.mssanz.org.au/modsim2013/D1/millikan.pdf M. Osipov. The influence of the numerical strength of engaged forces in their casualties. Translated by R. L. Helmbold and A. S. Rehm. Nav. Res. Log., 42:435–490, 1995. doi:10.1002/1520-6750(199504)42:3<435::AID-NAV3220420308>3.0.CO;2-2 R. Peterson. On the logarithmic law of combat and its application to tank combat. Oper. Res., 15:557–558, 1967. doi:10.1287/opre.15.3.557 A. H. Pincombe and B. M. Pincombe. Markov modelling of the effectiveness of arms sanctions: A case study of the Falklands War. ANZIAM J., 48:C527–C541, 2006. doi:10.21914/anziamj.v48i0.80 A. H. Pincombe and B. M. Pincombe. Tractable approximations to multistage decisions in air defence scenarios. ANZIAM J., 49:C273–C288, 2007. doi:10.21914/anziamj.v49i0.349 A. H. Pincombe, B. M. Pincombe and C. E. M. Pearce. Putting the art before the force. ANZIAM J., 51:C482–C496, 2010. doi:10.21914/anziamj.v51i0.2584. A. H. Pincombe, B. M. Pincombe and C. E. M. Pearce. A simple battle model with explanatory power. ANZIAM J., 51:C497–C511, 2010. doi:10.21914/anziamj.v51i0.2585 A. H. Pincombe and B. M. Pincombe. Dispersed combat as many-on-many search: Solving generalised Lanchester equations. ANZIAM J. to appear. doi:10.21914/anziamj.v57i0.10447 B. M. Pincombe and A. H. Pincombe. Scoping a flexible deployment framework using adversarial scenario analysis. Int. J. Intell. Def. Supp. Sys., 3(3/4):225–262, 2010. doi:10.1504/IJIDSS.2010.037092 B. M. Pincombe, S. Blunden, A. H. Pincombe and P. Dexter. Ascertaining a hierarchy of dimensions from time-poor experts: Linking tactical vignettes to strategic scenarios. Technol. Forecast. Soc., 80(4):584–598, 2013. doi:10.1016/j.techfore.2012.05.001 R. H. Scales. Firepower in limited war. National Defense University Press, Washington, DC, 1993. G. Smith. Battle atlas of the Falklands War 1982 by Land, Sea, and Air. Naval-History.net, Penarth, UK, 2006. http://www.naval-history.net/NAVAL1982FALKLANDS.htm G. Hubbard. HMS Yarmouth: Captains Diary. http://www.hms-yarmouth.com/co.diary.htm
Tractable approximations to multistage decisions in air defence scenarios
No full textSimulations are commonly used to investigate the control and resource allocation problems associated with pitting aircraft against ground based air defences. Such simulations rapidly become computationally intractable as units are added. Previous work described an envelope method that retains computational tractability if the lowest and highest cost target sequences can be defined a priori and used to establish solution bounds. This approach must be modified to be applied to the more common case where there are no obvious best or worst sequences of targets. We show that these bounding sequences can be approximated by using binary comparisons and by basing decisions on a heuristic. This approach compares well with exact results in some computationally tractable situations.
References R. E. Ball, The Fundamentals of Aircraft Combat Survivability Analysis and Design (American Institute of Aeronautics and Astronautics, 1985). D. Ghose, M. Krichman, J. L. Speyer and J. S. Shamma, Modeling and analysis of air campaign resource allocation: A spatio-temporal decomposition approach, IEEE Transactions on systems, man and cybernetics- Part A: Systems and humans 32 (2002) 403--418. Jose B. Cruz Jr, Marwan A. Simaan, Aga Gacic, Huihui Jiang, Bruno Letellier, Ming Li and Yong Liu, Game-theoretic modeling and control of a military air operation, IEEE Transactions on aerospace and electronic systems 37 (2001) 1393--1405. Eric V. Larson and Glenn A. Kent, A new methodology for assessing multilayer missile defence options, Monograph Report, RAND Corporation (1994) . W. McEneany, B. Fitzpatrick and I. Lauko, Stochastic game approach to air operations, IEEE Transactions on Aerospace and Electronic Systems 40 (2004) 1191--1216. A. H. Pincombe and B. M. Pincombe, A Markov decision model for tactical military engagements, Proceedings of ASOR2001 (2001) . A. H. Pincombe and B. M. Pincombe, A Markov based method for military analysis, Bulletin of the Australian Society for Operations Research 22 (2003) . A. H. Pincombe and B. M. Pincombe, Markov modelling on the effectiveness of sanctions: A case study of the Falklands war, in Proceedings of the 13th Biennial Computational Techniques and Applications Conference, CTAC-2006 (eds. Wayne Read and A. J. Roberts), Volume 48 of ANZIAM J., http://anziamj.austms.org.au/ojs/index.php/ANZIAMJ/article/view/80 [November 14, 2007], C527--C541. A. Tversky and I. Simonson, Context-dependent preferences, Management Science 39 (1993) 1179--1189. Yong Liu, Marwan A. Simaan and Jose B. Cruz Jr, An application of dynamic Nash task assignment strategies to multi-team military air operations, Automatica 39 (2003) 1469--1479
Dispersed combat as mass action with finite search
No full textImprovements to models of battle attrition are necessary because current models cannot explain battle attrition. Agent based simulations indicate that calculated attrition is substantially different when agents are not assumed to have unlimited detection capabilities. However, agent based models are limited to small force sizes and there is no evidence that the changes in calculated attrition occur for large force sizes. We develop a probabilistic model, based on Bernoulli trials, to check if limited detection capabilities result in significant changes to calculated attrition when force sizes are large, as in battle datasets. Our model is a search model and we convert it to an attrition model via the same processes used in current models, and include the same assumptions for factors other than detection range. We find two series solutions to the model, one for small force sizes, the other for large force sizes, and find numerically that the two solutions strongly overlap. The new model makes a difference to calculated attrition when force sizes are small, but not when they are large. However, the model makes a difference to calculated attrition for all force sizes if the battlefield area is increased to maintain a sparse force density. Our approach is mathematical, not requiring application knowledge, and several of the assumptions underlying mass action models are raised in our discussion.
References J. V. Chase. Sea fights: A mathematical investigation of the effect of superiority of force in combats upon the sea. Naval War College Archives, RG 8, Box 109, XTAV (1902), 1902. N. R. Franks and L. W. Partridge. Lanchester battles and the evolution of combat in ants. Anim. Behav., 45:197–199, 1993. doi:10.1006/anbe.1993.1021 G. S. Gradschtein and I. M. Ryzhik. Tables of Series, Products and Integrals. Deutcher Verlag der Wissenschaften, 1996. N. C. Grassly and C. Fraser. Mathematical models of infectious disease transmission. Nat. Rev. Microbiol., 6:477–487, 2008. doi:10.1038/nrmicro1845 D. Kahneman. Thinking Fast and Slow. Penguin, London, 2013. L. R. Kosowski, A. Pincombe and B. Pincombe. Irrelevance of the fractal dimension term in the modified fractal attrition equation. ANZIAM J., 52:C988–C1011, 2011. doi:10.21914/anziamj.v52i0.3963 F. W. Lanchester. Aircraft in warfare: The dawn of the fourth arm. Constable, London, 1916. http://edc448uri.wikispaces.com/file/view/Lanchester+-+Aircraft+in+Warfare.pdf T. W. Lucas and T. Turkes. Fitting Lanchester equations to the Battles of Kursk and Ardennes. Nav. Res. Log., 51:95–116, 2004. doi:10.1002/nav.10101 T. W. Lucas and J. A. Dinges. The effect of battle circumstances on fitting Lanchester equations to the Battle of Kursk. Mil. Oper. Res., 9:17–30, 2004. http://www.mors.org/Publications/MOR-Journal/Online-Issues P. M. Morse and G. E. Kimball. Methods of Operations Research. Wiley, 1951. M. Osipov. The influence of the numerical strength of engaged forces in their casualties. Translated by R. L. Helmbold and A. S. Rehm. Nav. Res. Log., 42:435–490, 1995. doi:10.1002/1520-6750(199504)42:3<435::AID-NAV3220420308>3.0.CO;2-2 R. Peterson. On the logarithmic law of combat and its application to tank combat. Oper. Res., 15:557–558, 1967. doi:10.1287/opre.15.3.557 A. H. Pincombe, B. M. Pincombe and C. E. M. Pearce, Putting the art before the force. ANZIAM J., 51:C482–C496, 2010. doi:10.0000/anziamj.v51i0.2584. A. H. Pincombe, B. M. Pincombe and C. E. M. Pearce. A simple battle model with explanatory power. ANZIAM J., 51:C497–C511, 2010. doi:10.21914/anziamj.v51i0.2585. B. M. Pincombe and A. H. Pincombe. Mass action models of Falklands War battles. ANZIAM J., 57:C235–C252, 2016. doi:10.21914/anziamj.v57i0.10450 J. G. Taylor. Lanchester models of warfare. Operations Research Society of America, Arlington, 1983
Putting the art before the force
No full textProceedings of EMAC 2009, held at the Unversity of Adelaide, 6-9th December 2009We use a dataset from the Battle of Kursk to test three estimators of attrition: linear, quadratic and log dependence on the number of soldiers in each force. Data giving force numbers per day show significant collinearity, so we use force and loss ratios for our tests. We demonstrate that the strongest correlate in the dataset for a sides attrition is its own force strength. This supports the log estimator, and we evaluate the proposition that this counterintuitive connection is a product of the pre-battle art of war, where commanders attempt to balance their forces to their expectations of threat. Thus expected losses generate actual force numbers whereas we seek information on the ways that force numbers generate actual losses, and both processes are based on the same correlation information. We argue that the dataset must still contain information on the mechanisms of attrition, so we widen our search criteria and uncover some remarkable facts. © Austral. Mathematical Soc. 2010.A. H. Pincombe, B. M. Pincombe and C. E. M. Pearc
Uncertainty in availability generated by inventory management controls in a generic repairable item sustainment system
No full textFor defence logistics, strategic planning is typically based on mean values. Supply flows are estimated from average throughputs, and supply chain resources are allocated to meet average demands. Operations management is also based on mean values. Mean-value based inventory management techniques are the preferred way to maintain the availability of spare parts. Recent research suggests that defence maintenance systems using such inventory management techniques are sensitive to stochastic variability in stock demand. We illustrate that these deliberate planning actions can lead to increased uncertainty in the prediction of output measures such as operational availability. We use Discrete Event Simulation as well as Design of Experiments methods to model a maintenance system for a single type of repairable item. We demonstrate that the inclusion of inventory management leads to increased average availability of spare parts for a vehicle fleet. However, in some cases the variation in availability decreases the system's apparent reliability.
References Anscombe, F. J. (1948) The Validity of Comparative Experiments. Journal of the Royal Statistical Society. Series A (General) 111 (3): 181--211. doi:10.2307/2984159 MR30181. Bender A., Pincombe A. H., Sherman G. D. (2009) Effects of decay uncertainty in the prediction of life-cycle costings for large scale military capability projects 18th World IMACS / MODSIM Congress, Cairns, Australia 13--17 July 2009. Brown, R. G Statistical Forecasting for Inventory Control McGraw-Hill, New York, 1959 Brown, Robert Goodell Smoothing Forecasting and Prediction of Discrete Time Series Englewood Cliffs, NJ: Prentice-Hall , 1963 Gardner, E. S., Jr., and McKenzie, E. Forecasting trends in time series Management Science, 31, 1237--1246, 1985 Jie Wan, Cong Zhao, Simulation Research on Multi-Echelon Inventory System in Supply Chain Based on Arena, icise, pp.397--400, First International Conference on Information Science and Engineering, 2009 Hartmut Bossel Systems and models: Complexity, Dynamics, Evolution, Sustainability Books on Demand GmbH, 2007 Piasecki, David J. Inventory Management Explained: A focus on Forecasting, Lot Sizing, Safety Stock, and Ordering Systems OPS Publishing, 2009. Sherman G. D., Pincombe A. H., Bender A. (2009) Determining some of the triggers for early life cycle failure in decay affected logistic queueing simulation, Proceedings of the 9th Biennial Engineering Mathematics and Applications Conference, EMAC-2009 ANZIAM J., 51(E):C715--C729, 2010. http://journal.austms.org.au/ojs/index.php/ANZIAMJ/article/view/2604
Determining some of the triggers for early life cycle failure in decay affected logistic queueing simulation
No full textLife-cycle cost estimates for large scale, long term, future military capabilities are difficult to make and subject to complexities. Usually they are generated from anecdotal experience. However, experience may not be a sound basis, so modelling and simulation are employed to define conditions that lead to early system failure in measures such as availability levels or the capability's life-of-type. Such models typically have common characteristics, including decay or degradation, queueing delays, availability of resources, and maintenance processes. Our generic model is a queue server, discrete event simulation that emulates macroscopic maintenance processes using time based parameters and statistical distributions. Previously we reported that the simulated system shows evidence of bifurcation-like behaviour in life-of-type estimates. This suggested that uncertainties in microscopic variables (such as inter-arrival times) cause instabilities in high level strategic performance indicators, making the prediction of such indicators difficult and bringing into question the use of mean based estimation methods for inventory provisioning. Our objective is to define the conditions which lead to system failure. We use a series of numerical simulation experiments to investigate and define such conditions. Outcomes show that system performance is sensitive to the types of input distribution used and that decay processes are strongly associated with complex behaviour even when most of the interacting factors of the real system have been removed from the simulation.
References Bender A., Pincombe A. and Sherman G. D., Effects of decay uncertainty in the prediction of life-cycle costing for large scale military capability projects 18th World IMACS / MODSIM Congress, Cairns, Australia 13--17 July 2009, http://mssanz.org.au/modsim09. Feichtinger G., Hommes C. H. and Herold W., Chaos in a Simple Deterministic Queueing System, ZOR - Mathematical Methods of Operations Research, 40, 1994, 109--119. doi:10.1007/BF01414032 Gavrilov L. A., Gavrilova, N. S., The reliability theory of ageing and longevity. Journal of Theoretical Biology, 213(4), 2001, 527--545. doi:10.1006/jtbi.2001.2430 Kleijnen, J. P. C., S. M. Sanchez, T. W. Lucas, and T. M. Cioppa, State-of-the-art review: a userÃs guide to the brave new world of designing simulation experiments. INFORMS Journal on Computing, 17, no. 3, 2005, 263--289. doi:10.1287/ijoc.1050.0136 Upadhya S. K. and Srinivasan N. K., Availability of Weapon Systems with Logistic Delays: A Simulation Approach, International Journal of Quality and Reliability Management 20:7, 2004, 836--846. doi:10.1108/02656710310491249 Verhulst, P. F., Recherches mathematiques sur la loi d'accroissement de la population., Nouv. mem. de l'Academie Royale des Sci. et Belles-Lettres de Bruxelles 18, 1845, 1--41
Rethinking assessment for the science modules in the first year nursing programme: Final project report
No full textThis project evaluated an innovative assessment tool that was developed to provide evidence that students were developing science-informed competence for nursing. Measuring and assessing competence in nursing education is a current world-wide concern, with few solutions offered (Anderson, 2008; Cowan et al., 2005; Lauder et al., 2008; Pincombe et al., 2007). At Waikato Institute of Technology, the prescription of Nursing Council of New Zealand (NCNZ) nursing competencies into the science modules of the Bachelor of Nursing curriculum commenced in 2009. Examination of the alignment of pedagogy, curriculum and assessment revealed that existing methods of assessment did not effectively assess all aspects of competence.
This research project investigated what tools could be used to assess evidence of the development of all aspects of science-informed competence in nursing education, and developed a new assessment tool. The tool was evaluated in terms of its construct, concurrent and consequential validity through a variety of data collection methods.
Findings indicated that the new assessment tool enabled assessment of all aspects of competence, including the contribution of student attitudes, values and abilities. It was also effective in providing students with opportunities to make links between science learning and nursing practice. Questionnaire and focus group results indicated that most students had some understanding of the purpose of the assessment tool and understood the practical test as linking to a ‘nursing perspective’. However, the students’ overall perception of the assessment was negative.
We concluded that this was influenced by three main variables; the length of the test, the readability and format of assessment items, and the perceived unfamiliarity of the assessment conditions (Cohen, Manion & Morrison, 2007). As a result of these findings, recommendations for practice and further research are offered
Midwives' experiences when working with third year midwifery students
No full textPurpose: Midwifery students require appropriate and timely access to clinical learning opportunities during their education toward a Bachelor of Midwifery and the quality of this clinical experience influences the student’s learning and confidence. To achieve this they must be supported by practising midwives. However at times midwives decline to work with students, citing a variety of reasons. To ensure the required quality and quantity of clinical placements the midwifery schools need to understand the barriers and enablers to midwives working effectively with third year midwifery students. Method: Midwives on the midwifery school’s database who regularly work with midwifery students were invited to participate in the research. Data was gathered through two focus groups of midwives who have worked with third year midwifery students. The transcripts were then thematically analysed. Findings: The midwives described their experiences when working with students. The first theme describes the midwives’ work with students and includes: that confidence thing, it’s not just about clinical skills and learning to be professional. The second theme describes the implications for midwives’ practice when working with students and includes: we are responsible, what is expected of me and wanting a break. Issues arising in professionalism weave through these themes. Implications: Students with poor knowledge levels and unprofessional behaviour were regarded as problematic for the midwives working with them. The midwives were frustrated when students could not see the bigger picture and did not appear to understand the expected professional behaviours and boundaries. The midwives enjoyed regular contact with the midwifery school to support them when working with students particularly concerning assessment of students. They also enjoyed the learning they gained from working alongside students which they found beneficial to their own practice knowledge. At times there were tensions between the needs of women and students, and as the midwife moved between her role as teacher, supporter and assessor of the student. However most placements were a positive experience for the midwives and they took pleasure in the student’s progression through the programme
