Instead of responding in the comments section, I have decided to respond with another blog post.
As the person points out, most Army simulations exist to “enable students/staff to maintain and improve readiness…improve their staff skills, SOPs, reporting procedures, and planning….”
Yes this true, but I argue that this does not obviate the need for accurate simulations. Assuming no change in complexity, I cannot think of a single scenario where having a less accurate model is more desirable that having a more accurate model.
Now what is missing from many of these models that I have seen? Often a realistic unit breakpoint methodology, a proper comparison of force ratios, a proper set of casualty rates, addressing human factors, and many other matters. Many of these things are being done in these simulations already, but are being done incorrectly. Quite simply, they do not realistically portray a range of historical or real combat examples.
He then quotes the 1997-1998 Simulation Handbook of the National Simulations Training Center:
The algorithms used in training simulations provide sufficient fidelity for training, not validation of war plans. This is due to the fact that important factors (leadership, morale, terrain, weather, level of training or units) and a myriad of human and environmental impacts are not modeled in sufficient detail….”
Let’s take their list made around 20 years ago. In the last 20 years, what significant quantitative studies have been done on the impact of leadership on combat? Can anyone list them? Can anyone point to even one? The same with morale or level of training of units. The Army has TRADOC, the Army Staff, Leavenworth, the War College, CAA and other agencies, and I have not seen in the last twenty years a quantitative study done to address these issues. And what of terrain and weather? They have been around for a long time.
Army simulations have been around since the late 1950s. So at the time these shortfalls are noted in 1997-1998, 40 years had passed. By their own admission, these issues had not been adequately addressed in the previous 40 years. I gather they have not been adequately in addressed in the last 20 years. So, the clock is ticking, 60 years of Army modeling and simulation, and no one has yet fully and properly address many of these issues. In many cases, they have not even gotten a good start in addressing them.
Anyhow, I have little interest in arguing these issues. My interest is in correcting them.
“If we maintain our faith in God, love of freedom, and superior global airpower, the future [of the US] looks good.” — U.S. Air Force General Curtis E. LeMay (Commander, U.S. Strategic Command, 1948-1957)
Curtis LeMay was involved in the formation of RAND Corporation after World War II. RAND created several models to measure the dynamics of the US-China military balance over time. Since 1996, this has been computed for two scenarios, differing by range from mainland China: one over Taiwan and the other over the Spratly Islands. The results of the model results for selected years can be seen in the graphic below.
The capabilities listed in the RAND study are interesting, notable in that the air superiority category, rough parity exists as of 2017. Also, the ability to attack air bases has given an advantage to the Chinese forces.
Investigating the methodology used does not yield any precise quantitative modeling examples, as would be expected in a rigorous academic effort, although there is some mention of statistics, simulation and historical examples.
The analysis presented here necessarily simplifies a great number of conflict characteristics. The emphasis throughout is on developing and assessing metrics in each area that provide a sense of the level of difficulty faced by each side in achieving its objectives. Apart from practical limitations, selectivity is driven largely by the desire to make the work transparent and replicable. Moreover, given the complexities and uncertainties in modern warfare, one could make the case that it is better to capture a handful of important dynamics than to present the illusion of comprehensiveness and precision. All that said, the analysis is grounded in recognized conclusions from a variety of historical sources on modern warfare, from the air war over Korea and Vietnam to the naval conflict in the Falklands and SAM hunting in Kosovo and Iraq. [Emphasis added].
We coded most of the scorecards (nine out of ten) using a five-color stoplight scheme to denote major or minor U.S. advantage, a competitive situation, or major or minor Chinese advantage. Advantage, in this case, means that one side is able to achieve its primary objectives in an operationally relevant time frame while the other side would have trouble in doing so. [Footnote] For example, even if the U.S. military could clear the skies of Chinese escort fighters with minimal friendly losses, the air superiority scorecard could be coded as “Chinese advantage” if the United States cannot prevail while the invasion hangs in the balance. If U.S. forces cannot move on to focus on destroying attacking strike and bomber aircraft, they cannot contribute to the larger mission of protecting Taiwan.
All of the dynamic modeling methodology (which involved a mix of statistical analysis, Monte Carlo simulation, and modified Lanchester equations) is publicly available and widely used by specialists at U.S. and foreign civilian and military universities.” [Emphasis added].
As TDI has contended before, the problem with using Lanchester’s equations is that, despite numerous efforts, no one has been able to demonstrate that they accurately represent real-world combat. So, even with statistics and simulation, how good are the results if they have relied on factors or force ratios with no relation to actual combat?
What about new capabilities?
As previously posted, the Kratos Mako Unmanned Combat Aerial Vehicle (UCAV), marketed as the “unmanned wingman,” has recently been cleared for export by the U.S. State Department. This vehicle is specifically oriented towards air-to-air combat, is stated to have unparalleled maneuverability, as it need not abide by limits imposed by human physiology. The Mako “offers fighter-like performance and is designed to function as a wingman to manned aircraft, as a force multiplier in contested airspace, or to be deployed independently or in groups of UASs. It is capable of carrying both weapons and sensor systems.” In addition, the Mako has the capability to be launched independently of a runway, as illustrated below. The price for these vehicles is three million each, dropping to two million each for an order of at least 100 units. Assuming a cost of $95 million for an F-35A, we can imagine a hypothetical combat scenario pitting two F-35As up against 100 of these Mako UCAVs in a drone swarm; a great example of the famous phrase, quantity has a quality all its own.
A battery of Kratos Aerial Target drone ready for take off. One of the advantages of the low-cost Kratos drones are their ability to get into the air quickly. [Kratos Defense]
How to evaluate the effects of these possible UCAV drone swarms?
In building up towards the analysis of all of these capabilities in the full theater, campaign level conflict, some supplemental wargaming may be useful. One game that takes a good shot at modeling these dynamics is Asian Fleet. This is a part of the venerable Fleet Series, published by Victory Games, designed by Joseph Balkoski to model modern (that is Cold War) naval combat. This game system has been extended in recent years, originally by Command Magazine Japan, and then later by Technical Term Gaming Company.
Screenshot of Asian Fleet module by Bryan Taylor [vassalengine.org]
Now, in the article by Michael Peck introducing C-WAM, there was a quote that got our attention:
“We tell everybody: Don’t focus on the various tactical outcomes,” Mahoney says. “We know they are wrong. They are just approximations. But they are good enough to say that at the operational level, ‘This is a good idea. This might work. That is a bad idea. Don’t do that.’”
I am sorry, but this line of argument has always bothered me.
While I understand that no model is perfect, that is the goal that modelers should always strive for. If the model is a poor representation of combat, or parts of combat, then what are you teaching the user? If the user is professional military, then is this negative training? Are you teaching them an incorrect understanding of combat? Will that understanding only be corrected after real combat and loss of American lives? This is not being melodramatic…..you fight as you train.
We have seen the argument made elsewhere that some models are only being used for training, so…….
I would like to again bring your attention to the “base of sand” problem:
As always, it seems that making the models more accurate seems to take lower precedence to whatever. Validating models tends to never be done. JICM has never been validated. COSAGE and ATCAL as used in JICM have never been validated. I don’t think C-WAM has ever been validated.
Just to be annoyingly preachy, I would like to again bring your attention to the issue of validation:
This week’s list of links is an odds-and-ends assortment.
David Vergun has an interview with General Stephen J. Townshend, commander of the U.S. Army Training and Doctrine Command (TRADOC) on the Army website about the need for smaller, lighter, and faster equipment for future warfare.
And finally, MeritTalk, a site focused on U.S. government information technology, has posted a piece, “Pentagon Wants An Early Warning System For Hybrid Warfare,” looking at the Defense Advanced Research Projects Agency’s (DARPA) ambitious Collection and Monitoring via Planning for Active Situational Scenarios (COMPASS) program, which will incorporate AI, game theory, modeling, and estimation technologies to attempt to decipher the often subtle signs that precede a full-scale attack.
In 1931, Lieutenant Colonel (later Brigadier General) Love, then a Medical Corps physician in the U.S. Army Medical Field Services School, published a study of American casualty data in the recent Great War, titled “War Casualties.”[1] This study was likely the source for tables used for casualty estimation by the U.S. Army through 1944.[2]
Love’s research was likely the basis for rate tables for calculating casualties that first appeared in the 1932 edition of the War Department’s Staff Officer’s Field Manual.[3]
Battle Casualties, including Killed, in Percent of Unit Strength, Staff Officer’s Field Manual (1932).
The 1932 Staff Officer’s Field Manual estimation methodology reflected Love’s sophisticated understanding of the factors influencing combat casualty rates. It showed that both the resistance and combat strength (and all of the factors that comprised it) of the enemy, as well as the equipment and state of training and discipline of the friendly troops had to be taken into consideration. The text accompanying the tables pointed out that loss rates in small units could be quite high and variable over time, and that larger formations took fewer casualties as a fraction of overall strength, and that their rates tended to become more constant over time. Casualties were not distributed evenly, but concentrated most heavily among the combat arms, and in the front-line infantry in particular. Attackers usually suffered higher loss rates than defenders. Other factors to be accounted for included the character of the terrain, the relative amount of artillery on each side, and the employment of gas.
The 1941 iteration of the Staff Officer’s Field Manual, now designated Field Manual (FM) 101-10[4], provided two methods for estimating battle casualties. It included the original 1932 Battle Casualties table, but the associated text no longer included the section outlining factors to be considered in calculating loss rates. This passage was moved to a note appended to a new table showing the distribution of casualties among the combat arms.
Rather confusingly, FM 101-10 (1941) presented a second table, Estimated Daily Losses in Campaign of Personnel, Dead and Evacuated, Per 1,000 of Actual Strength. It included rates for front line regiments and divisions, corps and army units, reserves, and attached cavalry. The rates were broken down by posture and tactical mission.
Estimated Daily Losses in Campaign of Personnel, Dead and Evacuated, Per 1,000 of Actual Strength, FM 101-10 (1941)
The source for this table is unknown, nor the method by which it was derived. No explanatory text accompanied it, but a footnote stated that “this table is intended primarily for use in school work and in field exercises.” The rates in it were weighted toward the upper range of the figures provided in the 1932 Battle Casualties table.
The October 1943 edition of FM 101-10 contained no significant changes from the 1941 version, except for the caveat that the 1932 Battle Casualties table “may or may not prove correct when applied to the present conflict.”
The October 1944 version of FM 101-10 incorporated data obtained from World War II experience.[5] While it also noted that the 1932 Battle Casualties table might not be applicable, the experiences of the U.S. II Corps in North Africa and one division in Italy were found to be in agreement with the table’s division and corps loss rates.
FM 101-10 (1944) included another new table, Estimate of Battle Losses for a Front-Line Division (in % of Actual Strength), meaning that it now provided three distinct methods for estimating battle casualties.
Estimate of Battle Losses for a Front-Line Division (in % of Actual Strength), FM 101-10 (1944)
Like the 1941 Estimated Daily Losses in Campaign table, the sources for this new table were not provided, and the text contained no guidance as to how or when it should be used. The rates it contained fell roughly within the span for daily rates for severe (6-8%) to maximum (12%) combat listed in the 1932 Battle Casualty table, but would produce vastly higher overall rates if applied consistently, much higher than the 1932 table’s 1% daily average.
FM 101-10 (1944) included a table showing the distribution of losses by branch for the theater based on experience to that date, except for combat in the Philippine Islands. The new chart was used in conjunction with the 1944 Estimate of Battle Losses for a Front-Line Division table to determine daily casualty distribution.
Distribution of Battle Losses–Theater of Operations, FM 101-10 (1944)
The final World War II version of FM 101-10 issued in August 1945[6] contained no new casualty rate tables, nor any revisions to the existing figures. It did finally effectively invalidate the 1932 Battle Casualties table by noting that “the following table has been developed from American experience in active operations and, of course, may not be applicable to a particular situation.” (original emphasis)
NOTES
[1] Albert G. Love, War Casualties, The Army Medical Bulletin, No. 24, (Carlisle Barracks, PA: 1931)
[2] This post is adapted from TDI, Casualty Estimation Methodologies Study, Interim Report (May 2005) (Altarum) (pp. 314-317).
[3] U.S. War Department, Staff Officer’s Field Manual, Part Two: Technical and Logistical Data (Government Printing Office, Washington, D.C., 1932)
[4] U.S. War Department, FM 101-10, Staff Officer’s Field Manual: Organization, Technical and Logistical Data (Washington, D.C., June 15, 1941)
[5] U.S. War Department, FM 101-10, Staff Officer’s Field Manual: Organization, Technical and Logistical Data (Washington, D.C., October 12, 1944)
[6] U.S. War Department, FM 101-10 Staff Officer’s Field Manual: Organization, Technical and Logistical Data (Washington, D.C., August 1, 1945)
One interceptor appears to have “pulled a u-turn” and exploded over Riyadh.
This interceptor may have been the source of the Saudi casualties (one dead, two injured)
This could be the largest barrage of missiles fired at Saudi Arabia by the Houthi’s yet.
I wonder what interceptor Saudi Arabia was using. I wonder if failure is common with most missile defense systems (the situation with North Korea comes to mind here).
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Update:
This is not the first time we have discussed this problem:
Stretcher bearers of the East Surrey Regiment, with a Churchill tank of the North Irish Horse in the background, during the attack on Longstop Hill, Tunisia, 23 April 1943. [Imperial War Museum/Wikimedia]
British Army staff officers during World War II and the 1950s used a set of look-up tables which listed expected monthly losses in percentage of strength for various arms under various combat conditions. The origin of the tables is not known, but they were officially updated twice, in 1942 by a committee chaired by Major General Evett, and in 1951-1955 by the Army Operations Research Group (AORG).[2]
The methodology was based on staff predictions of one of three levels of operational activity, “Intense,” “Normal,” and “Quiet.” These could be applied to an entire theater, or to individual divisions. The three levels were defined the same way for both the Evett Committee and AORG rates:
The rates were broken down by arm and rank, and included battle and nonbattle casualties.
Rates of Personnel Wastage Including Both Battle and Non-battle Casualties According to the Evett Committee of 1942. (Percent per 30 days).
The Evett Committee rates were criticized during and after the war. After British forces suffered twice the anticipated casualties at Anzio, the British 21st Army Group applied a “double intense rate” which was twice the Evett Committee figure and intended to apply to assaults. When this led to overestimates of casualties in Normandy, the double intense rate was discarded.
From 1951 to 1955, AORG undertook a study of casualty rates in World War II. Its analysis was based on casualty data from the following campaigns:
Northwest Europe, 1944
6-30 June – Beachhead offensive
1 July-1 September – Containment and breakout
1 October-30 December – Semi-static phase
9 February to 6 May – Rhine crossing and final phase
Italy, 1944
January to December – Fighting a relatively equal enemy in difficult country. Warfare often static.
January to February (Anzio) – Beachhead held against severe and well-conducted enemy counter-attacks.
North Africa, 1943
14 March-13 May – final assault
Northwest Europe, 1940
10 May-2 June – Withdrawal of BEF
Burma, 1944-45
From the first four cases, the AORG study calculated two sets of battle casualty rates as percentage of strength per 30 days. “Overall” rates included KIA, WIA, C/MIA. “Apparent rates” included these categories but subtracted troops returning to duty. AORG recommended that “overall” rates be used for the first three months of a campaign.
The Burma campaign data was evaluated differently. The analysts defined a “force wastage” category which included KIA, C/MIA, evacuees from outside the force operating area and base hospitals, and DNBI deaths. “Dead wastage” included KIA, C/MIA, DNBI dead, and those discharged from the Army as a result of injuries.
The AORG study concluded that the Evett Committee underestimated intense loss rates for infantry and armor during periods of very hard fighting and overestimated casualty rates for other arms. It recommended that if only one brigade in a division was engaged, two-thirds of the intense rate should be applied, if two brigades were engaged the intense rate should be applied, and if all brigades were engaged then the intense rate should be doubled. It also recommended that 2% extra casualties per month should be added to all the rates for all activities should the forces encounter heavy enemy air activity.[1]
The AORG study rates were as follows:
Recommended AORG Rates of Personnel Wastage. (Percent per 30 days).
If anyone has further details on the origins and activities of the Evett Committee and AORG, we would be very interested in finding out more on this subject.
NOTES
[1] This post is adapted from The Dupuy Institute, Casualty Estimation Methodologies Study, Interim Report (May 2005) (Altarum) (pp. 51-53).
[2] Rowland Goodman and Hugh Richardson. “Casualty Estimation in Open and Guerrilla Warfare.” (London: Directorate of Science (Land), U.K. Ministry of Defence, June 1995.), Appendix A.
The U.S. National Academies of Sciences, Engineering, and Medicine has issued a new report emphasizing the need for developing countermeasures against multiple small unmanned aerial aircraft systems (sUASs) — organized in coordinated groups, swarms, and collaborative groups — which could be used much sooner than the U.S. Army anticipates. [There is a summary here.]
National Defense University’s Frank Hoffman has a very good piece in the current edition of Parameters, “Will War’s Nature Change in the Seventh Military Revolution?,” that explores the potential implications of the combinations of robotics, artificial intelligence, and deep learning systems on the character and nature of war.
To follow on Chris’s recent post about U.S. Army